GetFreeCourses.Me-Udemy-Complete Machine Learning and Data Science Zero to Mastery

Creation Time	Aug. 11, 2025, 8:20 p.m.
Last Access Time	Jan. 18, 2026, 1:42 p.m.
File Size	13.3 GB
Keywords	and Me-Udemy-Complete Mastery Science Zero Machine to GetFreeCourses Learning Data
Total Requests	285
Total Files	634
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4 227.6 MB
9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4 190.2 MB
9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4 176.1 MB
17. Career Advice + Extra Bits/9. CWD Git + Github.mp4 176.1 MB
9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.mp4 175.5 MB
17. Career Advice + Extra Bits/3. What If I Don_t Have Enough Experience.mp4 161.0 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.mp4 159.1 MB
9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.mp4 158.4 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.mp4 146.2 MB
5. Data Science Environment Setup/5. Mac Environment Setup.mp4 144.4 MB
9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.mp4 143.3 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.mp4 142.3 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4 139.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/9. Finding Patterns 3.mp4 137.9 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.mp4 137.8 MB
9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 136.9 MB
9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.mp4 135.0 MB
17. Career Advice + Extra Bits/11. Contributing To Open Source.mp4 130.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.mp4 127.5 MB
5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4 125.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.mp4 123.7 MB
9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.mp4 121.8 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4 119.8 MB
9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).mp4 118.8 MB
17. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4 118.4 MB
9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.mp4 116.9 MB
9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.mp4 116.8 MB
17. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4 113.1 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/14. Tuning Hyperparameters.mp4 108.0 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4 106.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.mp4 105.5 MB
6. Pandas Data Analysis/9. Manipulating Data.mp4 105.0 MB
9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 104.8 MB
18. Learn Python/1. What Is A Programming Language.mp4 104.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/15. Tuning Hyperparameters 2.mp4 104.1 MB
5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.mp4 103.9 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.mp4 103.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/13. TuningImproving Our Model.mp4 102.8 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4 101.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4 100.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.mp4 99.9 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4 98.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/11. Choosing The Right Models.mp4 96.4 MB
9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 96.0 MB
9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.mp4 94.8 MB
18. Learn Python/16. Variables.mp4 93.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp4 93.5 MB
18. Learn Python/2. Python Interpreter.mp4 93.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.mp4 92.2 MB
9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 91.5 MB
7. NumPy/13. Exercise Nut Butter Store Sales.mp4 91.3 MB
6. Pandas Data Analysis/11. Manipulating Data 3.mp4 91.0 MB
9. Scikit-learn Creating Machine Learning Models/37. Improving A Machine Learning Model.mp4 90.9 MB
9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4 88.3 MB
9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).mp4 87.2 MB
9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).mp4 87.1 MB
9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data 2 (Regression).mp4 86.9 MB
6. Pandas Data Analysis/10. Manipulating Data 2.mp4 86.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 86.4 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/21. Reviewing The Project.mp4 86.1 MB
7. NumPy/16. Turn Images Into NumPy Arrays.mp4 85.9 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.mp4 85.8 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.mp4 85.7 MB
7. NumPy/12. Dot Product vs Element Wise.mp4 83.9 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.mp4 82.7 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4 82.2 MB
18. Learn Python/5. Python 2 vs Python 3.mp4 82.1 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4 82.0 MB
7. NumPy/8. Manipulating Arrays.mp4 80.7 MB
13. Data Engineering/9. Optional OLTP Databases.mp4 79.7 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/5. Getting Our Tools Ready.mp4 79.4 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.mp4 79.3 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.mp4 79.2 MB
7. NumPy/4. NumPy DataTypes and Attributes.mp4 79.0 MB
9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 4 (Confusion Matrix).mp4 77.7 MB
9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4 75.1 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4 74.7 MB
18. Learn Python/10. Numbers.mp4 72.7 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/10. Preparing Our Data For Machine Learning.mp4 72.6 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/17. Evaluating Our Model.mp4 71.6 MB
7. NumPy/7. Viewing Arrays and Matrices.mp4 70.6 MB
9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Regression Model 1 (R2 Score).mp4 70.4 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/6. Histograms And Subplots.mp4 69.7 MB
18. Learn Python/26. Built-In Functions + Methods.mp4 69.4 MB
7. NumPy/9. Manipulating Arrays 2.mp4 67.9 MB
5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.mp4 67.3 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp4 67.0 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.mp4 66.9 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/6. Exploring Our Data.mp4 66.9 MB
6. Pandas Data Analysis/13. How To Download The Course Assignments.mp4 66.8 MB
7. NumPy/5. Creating NumPy Arrays.mp4 66.8 MB
9. Scikit-learn Creating Machine Learning Models/20. Making Predictions With Our Model.mp4 66.5 MB
9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 2 (ROC Curve).mp4 66.0 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/19. Evaluating Our Model 3.mp4 64.8 MB
18. Learn Python/48. Sets 2.mp4 64.3 MB
18. Learn Python/3. How To Run Python Code.mp4 63.9 MB
9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp4 63.7 MB
9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 5 (Confusion Matrix).mp4 63.6 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/7. Finding Patterns.mp4 63.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/16. Tuning Hyperparameters 3.mp4 63.0 MB
18. Learn Python/34. List Methods.mp4 61.8 MB
3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.mp4 60.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 60.3 MB
18. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp4 59.7 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4 57.0 MB
9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model 2.mp4 56.8 MB
9. Scikit-learn Creating Machine Learning Models/19. Fitting A Model To The Data.mp4 56.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.mp4 55.5 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/12. Experimenting With Machine Learning Models.mp4 55.3 MB
9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 3 (MSE).mp4 54.9 MB
9. Scikit-learn Creating Machine Learning Models/21. predict() vs predict_proba().mp4 54.3 MB
7. NumPy/11. Reshape and Transpose.mp4 53.5 MB
9. Scikit-learn Creating Machine Learning Models/42. Saving And Loading A Model.mp4 52.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp4 52.0 MB
7. NumPy/6. NumPy Random Seed.mp4 51.9 MB
7. NumPy/10. Standard Deviation and Variance.mp4 51.2 MB
18. Learn Python/30. Exercise Password Checker.mp4 51.1 MB
9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 3 (ROC Curve).mp4 50.6 MB
18. Learn Python/28. Exercise Type Conversion.mp4 50.3 MB
18. Learn Python/32. List Slicing.mp4 49.9 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 49.5 MB
18. Learn Python/23. Formatted Strings.mp4 49.3 MB
18. Learn Python/24. String Indexes.mp4 49.2 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4 49.0 MB
5. Data Science Environment Setup/7. Windows Environment Setup.mp4 47.9 MB
18. Learn Python/4. Our First Python Program.mp4 47.2 MB
9. Scikit-learn Creating Machine Learning Models/22. Making Predictions With Our Model (Regression).mp4 44.9 MB
3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4 44.9 MB
2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4 42.6 MB
18. Learn Python/44. Dictionary Methods 2.mp4 42.4 MB
13. Data Engineering/2. What Is Data.mp4 42.2 MB
18. Learn Python/11. Math Functions.mp4 41.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/18. Evaluating Our Model 2.mp4 41.5 MB
1. Introduction/1. Course Outline.mp4 40.7 MB
9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4 40.6 MB
18. Learn Python/37. Common List Patterns.mp4 40.5 MB
18. Learn Python/7. Learning Python.mp4 38.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/7. Subplots Option 2.mp4 38.1 MB
5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 3.mp4 37.9 MB
18. Learn Python/47. Sets.mp4 37.0 MB
3. Machine Learning and Data Science Framework/7. Features In Data.mp4 36.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/2. Project Overview.mp4 34.4 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp4 32.9 MB
7. NumPy/15. Sorting Arrays.mp4 32.8 MB
18. Learn Python/40. Dictionaries.mp4 32.7 MB
13. Data Engineering/7. Types Of Databases.mp4 32.6 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/2. Matplotlib Introduction.mp4 31.5 MB
9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Classification Model 1 (Accuracy).mp4 31.4 MB
18. Learn Python/19. Strings.mp4 31.0 MB
5. Data Science Environment Setup/4. Conda Environments.mp4 30.6 MB
2. Machine Learning 101/4. How Did We Get Here.mp4 30.5 MB
3. Machine Learning and Data Science Framework/5. Types of Data.mp4 29.3 MB
18. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp4 29.2 MB
18. Learn Python/8. Python Data Types.mp4 28.8 MB
18. Learn Python/36. List Methods 3.mp4 27.7 MB
3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp4 27.5 MB
6. Pandas Data Analysis/3. Pandas Introduction.mp4 27.4 MB
18. Learn Python/35. List Methods 2.mp4 27.4 MB
3. Machine Learning and Data Science Framework/13. Tools We Will Use.mp4 27.3 MB
18. Learn Python/43. Dictionary Methods.mp4 27.2 MB
7. NumPy/2. NumPy Introduction.mp4 26.8 MB
18. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp4 26.6 MB
7. NumPy/14. Comparison Operators.mp4 26.4 MB
18. Learn Python/6. Exercise How Does Python Work.mp4 26.0 MB
18. Learn Python/45. Tuples.mp4 25.6 MB
2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 25.5 MB
13. Data Engineering/5. What Is A Data Engineer 3.mp4 24.3 MB
13. Data Engineering/4. What Is A Data Engineer 2.mp4 24.2 MB
3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp4 23.5 MB
3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.mp4 23.2 MB
18. Learn Python/22. Escape Sequences.mp4 23.2 MB
2. Machine Learning 101/6. Types of Machine Learning.mp4 22.7 MB
19. Learn Python Part 2/43. Exercise Comprehensions.mp4 22.0 MB
18. Learn Python/31. Lists.mp4 22.0 MB
18. Learn Python/15. Optional bin() and complex.mp4 21.9 MB
19. Learn Python Part 2/30. Exercise Functions.mp4 21.8 MB
3. Machine Learning and Data Science Framework/12. Experimentation.mp4 21.3 MB
18. Learn Python/25. Immutability.mp4 20.8 MB
18. Learn Python/42. Dictionary Keys.mp4 20.4 MB
2. Machine Learning 101/2. AIMachine LearningData Science.mp4 19.7 MB
2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp4 19.4 MB
5. Data Science Environment Setup/2. Introducing Our Tools.mp4 19.3 MB
13. Data Engineering/13. Kafka and Stream Processing.mp4 19.2 MB
18. Learn Python/33. Matrix.mp4 19.1 MB
18. Learn Python/21. Type Conversion.mp4 19.0 MB
3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp4 17.8 MB
18. Learn Python/46. Tuples 2.mp4 17.0 MB
2. Machine Learning 101/1. What Is Machine Learning.mp4 16.9 MB
18. Learn Python/27. Booleans.mp4 16.5 MB
9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp4 16.5 MB
3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp4 16.0 MB
17. Career Advice + Extra Bits/7. JTS Start With Why.mp4 15.4 MB
18. Learn Python/18. Augmented Assignment Operator.mp4 15.3 MB
13. Data Engineering/3. What Is A Data Engineer.mp4 15.2 MB
13. Data Engineering/6. What Is A Data Engineer 4.mp4 14.9 MB
18. Learn Python/13. Operator Precedence.mp4 14.4 MB
18. Learn Python/38. List Unpacking.mp4 13.9 MB
13. Data Engineering/1. Data Engineering Introduction.mp4 13.5 MB
3. Machine Learning and Data Science Framework/1. Section Overview.mp4 13.3 MB
7. NumPy/1. Section Overview.mp4 13.3 MB
5. Data Science Environment Setup/3. What is Conda.mp4 12.5 MB
9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp4 12.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp4 12.3 MB
3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp4 11.4 MB
17. Career Advice + Extra Bits/6. JTS Learn to Learn.mp4 11.1 MB
21. Where To Go From Here/2. Thank You.mp4 11.1 MB
18. Learn Python/17. Expressions vs Statements.mp4 11.0 MB
6. Pandas Data Analysis/1. Section Overview.mp4 10.9 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/1. Section Overview.mp4 10.2 MB
13. Data Engineering/11. Hadoop, HDFS and MapReduce.mp4 10.1 MB
4. The 2 Paths/1. The 2 Paths.mp4 9.8 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp4 8.9 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/1. Section Overview.mp4 8.6 MB
1. Introduction/4. Your First Day.mp4 8.2 MB
18. Learn Python/39. None.mp4 7.9 MB
18. Learn Python/20. String Concatenation.mp4 7.3 MB
7. NumPy/16.2 numpy-images.zip.zip 7.3 MB
13. Data Engineering/12. Apache Spark and Apache Flink.mp4 5.8 MB
2. Machine Learning 101/9. Section Review.mp4 2.5 MB
5. Data Science Environment Setup/1. Section Overview.mp4 2.3 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/4.2 matplotlib-anatomy-of-a-plot-with-code.png.png 654.8 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/4.1 matplotlib-anatomy-of-a-plot.png.png 369.4 KB
6. Pandas Data Analysis/10.1 pandas-anatomy-of-a-dataframe.png.png 333.2 KB
6. Pandas Data Analysis/4.1 pandas-anatomy-of-a-dataframe.png.png 333.2 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4.jpg 214.5 KB
5. Data Science Environment Setup/3.4 conda-cheatsheet.pdf.pdf 201.3 KB
9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.srt 31.7 KB
5. Data Science Environment Setup/8. Windows Environment Setup 2.srt 31.6 KB
9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.srt 30.5 KB
6. Pandas Data Analysis/9.1 car-sales-extended-missing-data.csv.csv 30.2 KB
9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.srt 26.4 KB
9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.srt 25.5 KB
5. Data Science Environment Setup/5. Mac Environment Setup.srt 23.9 KB
9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt 23.1 KB
9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.srt 22.7 KB
5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.srt 22.5 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.srt 22.3 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.srt 22.3 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.srt 22.3 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.srt 22.1 KB
9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.srt 21.4 KB
17. Career Advice + Extra Bits/9. CWD Git + Github.srt 21.2 KB
5. Data Science Environment Setup/6. Mac Environment Setup 2.srt 20.7 KB
17. Career Advice + Extra Bits/3. What If I Don_t Have Enough Experience.srt 20.0 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.srt 20.0 KB
7. NumPy/4. NumPy DataTypes and Attributes.srt 19.2 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/9. Finding Patterns 3.srt 18.9 KB
9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.srt 18.8 KB
17. Career Advice + Extra Bits/10. CWD Git + Github 2.srt 18.2 KB
6. Pandas Data Analysis/9. Manipulating Data.srt 18.1 KB
9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.srt 18.0 KB
6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.srt 17.9 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.srt 17.8 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/13. TuningImproving Our Model.srt 17.6 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.srt 17.3 KB
9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).srt 17.3 KB
17. Career Advice + Extra Bits/11. Contributing To Open Source.srt 17.1 KB
9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).srt 17.1 KB
9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.srt 17.0 KB
7. NumPy/13. Exercise Nut Butter Store Sales.srt 17.0 KB
9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.srt 16.9 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.srt 16.9 KB
6. Pandas Data Analysis/4. Series, Data Frames and CSVs.srt 16.8 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.srt 16.6 KB
9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.srt 16.3 KB
7. NumPy/8. Manipulating Arrays.srt 16.2 KB
9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.srt 16.1 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.srt 16.1 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.srt 16.0 KB
18. Learn Python/16. Variables.srt 16.0 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.srt 15.9 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/14. Tuning Hyperparameters.srt 15.7 KB
19. Learn Python Part 2/2. Conditional Logic.srt 15.7 KB
7. NumPy/12. Dot Product vs Element Wise.srt 15.3 KB
5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.srt 15.1 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/17. Evaluating Our Model.srt 15.1 KB
9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 4 (Confusion Matrix).srt 15.1 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/15. Tuning Hyperparameters 2.srt 15.1 KB
19. Learn Python Part 2/24. return.srt 15.0 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.srt 14.9 KB
9. Scikit-learn Creating Machine Learning Models/37. Improving A Machine Learning Model.srt 14.9 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/5. Scatter Plot And Bar Plot.srt 14.7 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.srt 14.6 KB
6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.srt 14.6 KB
9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).srt 14.6 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.srt 14.4 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.srt 14.2 KB
3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.srt 14.0 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.srt 14.0 KB
6. Pandas Data Analysis/10. Manipulating Data 2.srt 13.8 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/21. Reviewing The Project.srt 13.8 KB
6. Pandas Data Analysis/11. Manipulating Data 3.srt 13.7 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.srt 13.6 KB
6. Pandas Data Analysis/6. Describing Data with Pandas.srt 13.6 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.srt 13.5 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/7. Finding Patterns.srt 13.4 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.srt 13.3 KB
3. Machine Learning and Data Science Framework/11. Modelling - Comparison.srt 13.1 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/11. Choosing The Right Models.srt 13.0 KB
7. NumPy/7. Viewing Arrays and Matrices.srt 12.9 KB
9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).srt 12.9 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/5. Getting Our Tools Ready.srt 12.8 KB
19. Learn Python Part 2/45. Modules in Python.srt 12.7 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.srt 12.7 KB
19. Learn Python Part 2/48. Packages in Python.srt 12.5 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/6. Histograms And Subplots.srt 12.4 KB
7. NumPy/5. Creating NumPy Arrays.srt 12.4 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.srt 12.4 KB
9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 2 (ROC Curve).srt 12.3 KB
13. Data Engineering/9. Optional OLTP Databases.srt 12.1 KB
9. Scikit-learn Creating Machine Learning Models/20. Making Predictions With Our Model.srt 12.1 KB
9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.srt 12.1 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/10. Preparing Our Data For Machine Learning.srt 12.0 KB
9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Regression Model 1 (R2 Score).srt 12.0 KB
9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data 2 (Regression).srt 12.0 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.srt 11.6 KB
9. Scikit-learn Creating Machine Learning Models/21. predict() vs predict_proba().srt 11.6 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/19. Evaluating Our Model 3.srt 11.5 KB
7. NumPy/9. Manipulating Arrays 2.srt 11.5 KB
5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 3.srt 11.5 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.srt 11.5 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/6. Exploring Our Data.srt 11.4 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.srt 11.4 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.srt 11.2 KB
9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 5 (Confusion Matrix).srt 11.2 KB
18. Learn Python/10. Numbers.srt 11.1 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.srt 11.1 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/6.1 heart-disease.csv.csv 11.1 KB
5. Data Science Environment Setup/10.1 heart-disease.csv.csv 11.1 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/13.1 heart-disease.csv.csv 11.1 KB
6. Pandas Data Analysis/13. How To Download The Course Assignments.srt 11.1 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.srt 11.0 KB
18. Learn Python/34. List Methods.srt 10.8 KB
9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.srt 10.6 KB
19. Learn Python Part 2/47. Optional PyCharm.srt 10.5 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.srt 10.5 KB
7. NumPy/16. Turn Images Into NumPy Arrays.srt 10.4 KB
19. Learn Python Part 2/18. Our First GUI.srt 10.4 KB
18. Learn Python/26. Built-In Functions + Methods.srt 10.3 KB
17. Career Advice + Extra Bits/12. Contributing To Open Source 2.srt 10.2 KB
9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.srt 10.1 KB
19. Learn Python Part 2/36. Pure Functions.srt 10.1 KB
9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 3 (ROC Curve).srt 10.0 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/2. Project Overview.srt 10.0 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/16. Tuning Hyperparameters 3.srt 9.9 KB
9. Scikit-learn Creating Machine Learning Models/42. Saving And Loading A Model.srt 9.8 KB
7. NumPy/6. NumPy Random Seed.srt 9.7 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/12. Experimenting With Machine Learning Models.srt 9.6 KB
7. NumPy/11. Reshape and Transpose.srt 9.5 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.srt 9.4 KB
19. Learn Python Part 2/41. List Comprehensions.srt 9.4 KB
7. NumPy/10. Standard Deviation and Variance.srt 9.3 KB
9. Scikit-learn Creating Machine Learning Models/19. Fitting A Model To The Data.srt 9.3 KB
18. Learn Python/48. Sets 2.srt 9.2 KB
9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 3 (MSE).srt 9.2 KB
18. Learn Python/24. String Indexes.srt 9.2 KB
19. Learn Python Part 2/21. Functions.srt 9.2 KB
1. Introduction/1. Course Outline.srt 9.2 KB
9. Scikit-learn Creating Machine Learning Models/22. Making Predictions With Our Model (Regression).srt 9.1 KB
18. Learn Python/4. Our First Python Program.srt 9.0 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/9. Plotting From Pandas DataFrames.srt 9.0 KB
9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model 2.srt 9.0 KB
18. Learn Python/23. Formatted Strings.srt 8.8 KB
7. NumPy/15. Sorting Arrays.srt 8.8 KB
2. Machine Learning 101/1. What Is Machine Learning.srt 8.7 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.srt 8.6 KB
18. Learn Python/28. Exercise Type Conversion.srt 8.6 KB
18. Learn Python/32. List Slicing.srt 8.5 KB
19. Learn Python Part 2/32. Scope Rules.srt 8.5 KB
18. Learn Python/47. Sets.srt 8.4 KB
19. Learn Python Part 2/8. Exercise Logical Operators.srt 8.4 KB
19. Learn Python Part 2/40. reduce().srt 8.4 KB
13. Data Engineering/7. Types Of Databases.srt 8.4 KB
18. Learn Python/2. Python Interpreter.srt 8.3 KB
18. Learn Python/5. Python 2 vs Python 3.srt 8.2 KB
19. Learn Python Part 2/9. is vs ==.srt 8.1 KB
19. Learn Python Part 2/7. Logical Operators.srt 8.1 KB
2. Machine Learning 101/3. Exercise Machine Learning Playground.srt 8.1 KB
19. Learn Python Part 2/29. args and kwargs.srt 8.1 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/2. Matplotlib Introduction.srt 8.0 KB
18. Learn Python/30. Exercise Password Checker.srt 7.9 KB
19. Learn Python Part 2/19. DEVELOPER FUNDAMENTALS IV.srt 7.8 KB
3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.srt 7.7 KB
5. Data Science Environment Setup/7. Windows Environment Setup.srt 7.6 KB
13. Data Engineering/2. What Is Data.srt 7.6 KB
19. Learn Python Part 2/10. For Loops.srt 7.5 KB
7. NumPy/2. NumPy Introduction.srt 7.5 KB
19. Learn Python Part 2/49. Different Ways To Import.srt 7.5 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/18. Evaluating Our Model 2.srt 7.4 KB
19. Learn Python Part 2/15. While Loops.srt 7.4 KB
18. Learn Python/44. Dictionary Methods 2.srt 7.1 KB
9. Scikit-learn Creating Machine Learning Models/34. Machine Learning Model Evaluation.html 7.1 KB
18. Learn Python/40. Dictionaries.srt 7.1 KB
2. Machine Learning 101/4. How Did We Get Here.srt 7.1 KB
18. Learn Python/1. What Is A Programming Language.srt 7.0 KB
19. Learn Python Part 2/11. Iterables.srt 6.9 KB
3. Machine Learning and Data Science Framework/7. Features In Data.srt 6.8 KB
19. Learn Python Part 2/33. global Keyword.srt 6.7 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.srt 6.7 KB
3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.srt 6.6 KB
19. Learn Python Part 2/42. Set Comprehensions.srt 6.6 KB
3. Machine Learning and Data Science Framework/5. Types of Data.srt 6.5 KB
18. Learn Python/3. How To Run Python Code.srt 6.5 KB
9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.srt 6.4 KB
19. Learn Python Part 2/16. While Loops 2.srt 6.4 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/7. Subplots Option 2.srt 6.4 KB
2. Machine Learning 101/2. AIMachine LearningData Science.srt 6.4 KB
9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.srt 6.3 KB
13. Data Engineering/4. What Is A Data Engineer 2.srt 6.3 KB
18. Learn Python/19. Strings.srt 6.3 KB
19. Learn Python Part 2/37. map().srt 6.3 KB
3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.srt 6.2 KB
5. Data Science Environment Setup/4. Conda Environments.srt 6.1 KB
2. Machine Learning 101/8. What Is Machine Learning Round 2.srt 6.1 KB
3. Machine Learning and Data Science Framework/13. Tools We Will Use.srt 6.0 KB
19. Learn Python Part 2/4. Truthy vs Falsey.srt 6.0 KB
19. Learn Python Part 2/23. Default Parameters and Keyword Arguments.srt 6.0 KB
9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Classification Model 1 (Accuracy).srt 5.9 KB
19. Learn Python Part 2/13. range().srt 5.9 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/19. Saving And Sharing Your Plots.srt 5.8 KB
18. Learn Python/37. Common List Patterns.srt 5.8 KB
9. Scikit-learn Creating Machine Learning Models/32. Evaluating A Regression Model 2 (MAE).srt 5.7 KB
18. Learn Python/45. Tuples.srt 5.7 KB
2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.srt 5.7 KB
18. Learn Python/31. Lists.srt 5.6 KB
18. Learn Python/11. Math Functions.srt 5.4 KB
13. Data Engineering/5. What Is A Data Engineer 3.srt 5.4 KB
19. Learn Python Part 2/28. Clean Code.srt 5.4 KB
18. Learn Python/29. DEVELOPER FUNDAMENTALS II.srt 5.3 KB
19. Learn Python Part 2/3. Indentation In Python.srt 5.3 KB
2. Machine Learning 101/6. Types of Machine Learning.srt 5.3 KB
1. Introduction/4. Your First Day.srt 5.3 KB
18. Learn Python/43. Dictionary Methods.srt 5.3 KB
7. NumPy/14. Comparison Operators.srt 5.3 KB
19. Learn Python Part 2/17. break, continue, pass.srt 5.3 KB
19. Learn Python Part 2/26. Methods vs Functions.srt 5.2 KB
18. Learn Python/12. DEVELOPER FUNDAMENTALS I.srt 5.2 KB
18. Learn Python/8. Python Data Types.srt 5.2 KB
19. Learn Python Part 2/38. filter().srt 5.0 KB
13. Data Engineering/13. Kafka and Stream Processing.srt 5.0 KB
18. Learn Python/36. List Methods 3.srt 5.0 KB
18. Learn Python/22. Escape Sequences.srt 5.0 KB
3. Machine Learning and Data Science Framework/12. Experimentation.srt 5.0 KB
19. Learn Python Part 2/43. Exercise Comprehensions.srt 4.9 KB
13. Data Engineering/3. What Is A Data Engineer.srt 4.9 KB
19. Learn Python Part 2/22. Parameters and Arguments.srt 4.9 KB
3. Machine Learning and Data Science Framework/10. Modelling - Tuning.srt 4.9 KB
19. Learn Python Part 2/5. Ternary Operator.srt 4.8 KB
18. Learn Python/15. Optional bin() and complex.srt 4.8 KB
19. Learn Python Part 2/35. Why Do We Need Scope.srt 4.8 KB
4. The 2 Paths/1. The 2 Paths.srt 4.7 KB
13. Data Engineering/11. Hadoop, HDFS and MapReduce.srt 4.7 KB
19. Learn Python Part 2/30. Exercise Functions.srt 4.7 KB
3. Machine Learning and Data Science Framework/1. Section Overview.srt 4.7 KB
19. Learn Python Part 2/14. enumerate().srt 4.6 KB
18. Learn Python/35. List Methods 2.srt 4.5 KB
19. Learn Python Part 2/6. Short Circuiting.srt 4.5 KB
19. Learn Python Part 2/20. Exercise Find Duplicates.srt 4.4 KB
5. Data Science Environment Setup/2. Introducing Our Tools.srt 4.3 KB
3. Machine Learning and Data Science Framework/6. Types of Evaluation.srt 4.3 KB
19. Learn Python Part 2/27. Docstrings.srt 4.3 KB
13. Data Engineering/1. Data Engineering Introduction.srt 4.3 KB
18. Learn Python/42. Dictionary Keys.srt 4.2 KB
18. Learn Python/33. Matrix.srt 4.1 KB
9. Scikit-learn Creating Machine Learning Models/1. Section Overview.srt 4.1 KB
19. Learn Python Part 2/34. nonlocal Keyword.srt 4.1 KB
18. Learn Python/27. Booleans.srt 3.9 KB
13. Data Engineering/6. What Is A Data Engineer 4.srt 3.9 KB
19. Learn Python Part 2/31. Scope.srt 3.8 KB
6. Pandas Data Analysis/1. Section Overview.srt 3.7 KB
3. Machine Learning and Data Science Framework/2. Introducing Our Framework.srt 3.7 KB
21. Where To Go From Here/2. Thank You.srt 3.6 KB
18. Learn Python/41. DEVELOPER FUNDAMENTALS III.srt 3.6 KB
19. Learn Python Part 2/12. Exercise Tricky Counter.srt 3.6 KB
18. Learn Python/13. Operator Precedence.srt 3.5 KB
18. Learn Python/25. Immutability.srt 3.5 KB
5. Data Science Environment Setup/3. What is Conda.srt 3.4 KB
19. Learn Python Part 2/39. zip().srt 3.3 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/1. Section Overview.srt 3.1 KB
7. NumPy/1. Section Overview.srt 3.1 KB
9. Scikit-learn Creating Machine Learning Models/41. Quick Tip Correlation Analysis.srt 3.1 KB
18. Learn Python/21. Type Conversion.srt 3.1 KB
18. Learn Python/46. Tuples 2.srt 3.1 KB
19. Learn Python Part 2/1. Breaking The Flow.srt 3.0 KB
17. Career Advice + Extra Bits/7. JTS Start With Why.srt 3.0 KB
18. Learn Python/18. Augmented Assignment Operator.srt 3.0 KB
18. Learn Python/38. List Unpacking.srt 2.9 KB
18. Learn Python/6. Exercise How Does Python Work.srt 2.9 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/1. Section Overview.srt 2.7 KB
18. Learn Python/7. Learning Python.srt 2.6 KB
1. Introduction/3. Exercise Meet The Community.html 2.5 KB
17. Career Advice + Extra Bits/6. JTS Learn to Learn.srt 2.5 KB
2. Machine Learning 101/9. Section Review.srt 2.3 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/8. Quick Tip Data Visualizations.srt 2.3 KB
13. Data Engineering/12. Apache Spark and Apache Flink.srt 2.3 KB
18. Learn Python/39. None.srt 2.2 KB
1. Introduction/2. Join Our Online Classroom!.html 2.2 KB
7. NumPy/17. Assignment NumPy Practice.html 2.2 KB
5. Data Science Environment Setup/1. Section Overview.srt 2.1 KB
9. Scikit-learn Creating Machine Learning Models/46. Scikit-Learn Practice.html 2.1 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/20. Assignment Matplotlib Practice.html 2.1 KB
6. Pandas Data Analysis/12. Assignment Pandas Practice.html 2.1 KB
9. Scikit-learn Creating Machine Learning Models/17. Quick Tip How ML Algorithms Work.srt 1.9 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.srt 1.8 KB
18. Learn Python/17. Expressions vs Statements.srt 1.7 KB
22. Extras/1. Bonus Special Thank You Gift.html 1.6 KB
17. Career Advice + Extra Bits/14. Exercise Contribute To Open Source.html 1.4 KB
18. Learn Python/20. String Concatenation.srt 1.4 KB
7. NumPy/3. Quick Note Correction In Next Video.html 1.2 KB
19. Learn Python Part 2/44. Python Exam Testing Your Understanding.html 1.1 KB
6. Pandas Data Analysis/5. Data from URLs.html 1.1 KB
5. Data Science Environment Setup/9. Linux Environment Setup.html 1.0 KB
7. NumPy/18. Optional Extra NumPy resources.html 1.0 KB
9. Scikit-learn Creating Machine Learning Models/5. Quick Note Upcoming Videos.html 1018 bytes
3. Machine Learning and Data Science Framework/14. Optional Elements of AI.html 975 bytes
19. Learn Python Part 2/50. Next Steps.html 959 bytes
17. Career Advice + Extra Bits/13. Coding Challenges.html 948 bytes
21. Where To Go From Here/1. Become An Alumni.html 944 bytes
6. Pandas Data Analysis/2. Downloading Workbooks and Assignments.html 774 bytes
10. Supervised Learning Classification + Regression/1. Milestone Projects!.html 738 bytes
20. Bonus Learn Advanced Statistics and Mathematics for FREE!/1. Statistics and Mathematics.html 710 bytes
17. Career Advice + Extra Bits/1. Endorsements On LinkedIn.html 688 bytes
18. Learn Python/14. Exercise Operator Precedence.html 683 bytes
8. Matplotlib + Seaborn Plotting and Data Visualization/10. Quick Note Regular Expressions.html 632 bytes
17. Career Advice + Extra Bits/2. Quick Note Upcoming Video.html 587 bytes
17. Career Advice + Extra Bits/5. Quick Note Upcoming Videos.html 565 bytes
13. Data Engineering/8. Quick Note Upcoming Video.html 481 bytes
4. The 2 Paths/2. Python Developer Monthly.html 476 bytes
19. Learn Python Part 2/46. Quick Note Upcoming Videos.html 448 bytes
13. Data Engineering/10. Optional Learn SQL.html 410 bytes
19. Learn Python Part 2/25. Exercise Tesla.html 402 bytes
9. Scikit-learn Creating Machine Learning Models/3. Quick Note Upcoming Video.html 390 bytes
6. Pandas Data Analysis/7.1 car-sales.csv.csv 369 bytes
17. Career Advice + Extra Bits/8. Quick Note Upcoming Videos.html 352 bytes
17. Career Advice + Extra Bits/4. Learning Guideline.html 310 bytes
18. Learn Python/9. How To Succeed.html 280 bytes
11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.txt 239 bytes
9. Scikit-learn Creating Machine Learning Models/16. Quick Note Decision Trees.html 221 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/19.2 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.1 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/19.1 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.3 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 bytes
11. Milestone Project 1 Supervised Learning (Binary Classification)/2.1 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 bytes
11. Milestone Project 1 Supervised Learning (Binary Classification)/21.2 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 bytes
16. UPLOADED BY FEB 14th Storytelling + Communication How To Present Your Projects/1. This section will be done by FEB 14th.html 203 bytes
14. UPLOADED BY FEB 7! - Neural Networks Deep Learning + Transfer Learning/1. This section will be done by FEB 7th.html 202 bytes
15. UPLOADED BY FEB 7! - TensorFlow 2.0/1. This section will be done by FEB 7th.html 202 bytes
11. Milestone Project 1 Supervised Learning (Binary Classification)/2.3 End-to-end Heart Disease Classification Notebook (with annotations).html 201 bytes
11. Milestone Project 1 Supervised Learning (Binary Classification)/21.1 End-to-end Heart Disease Classification Notebook (with annotations).html 201 bytes
9. Scikit-learn Creating Machine Learning Models/2.1 Introduction to Scikit-Learn Jupyter Notebook (from the upcoming videos).html 197 bytes
9. Scikit-learn Creating Machine Learning Models/45.2 Introduction to Scikit-Learn Jupyter Notebook (from the videos).html 197 bytes
8. Matplotlib + Seaborn Plotting and Data Visualization/19.1 Introduction to Matplotlib Notebook (from the videos).html 195 bytes
8. Matplotlib + Seaborn Plotting and Data Visualization/2.1 Introduction to Matplotlib Jupyter Notebook (from the upcoming videos).html 195 bytes
9. Scikit-learn Creating Machine Learning Models/6.1 Scikit-Learn Reference Notebook.html 194 bytes
9. Scikit-learn Creating Machine Learning Models/7.1 Example Scikit-Learn Workflow Notebook.html 192 bytes
6. Pandas Data Analysis/11.2 Introduction to Pandas Jupyter Notebook (from the videos).html 191 bytes
6. Pandas Data Analysis/3.3 Introduction to Pandas Jupyter Notebook (from the upcoming videos).html 191 bytes
9. Scikit-learn Creating Machine Learning Models/2.3 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 bytes
9. Scikit-learn Creating Machine Learning Models/45.1 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 bytes
7. NumPy/16.3 Introduction to NumPy Jupyter Notebook (from the videos).html 190 bytes
7. NumPy/2.2 Introduction to NumPy Jupyter Notebook (from the upcoming videos).html 190 bytes
6. Pandas Data Analysis/11.1 Introduction to Pandas Jupyter Notebook (with annotations).html 185 bytes
6. Pandas Data Analysis/3.2 Introduction to Pandas Jupyter Notebook (with annotations).html 185 bytes
7. NumPy/16.1 Introduction to NumPy Jupyter Notebook (with annotations).html 184 bytes
7. NumPy/2.3 Introduction to NumPy Jupyter Notebook (with annotations).html 184 bytes
21. Where To Go From Here/How you can help GetFreeCourses.Me.txt 182 bytes
How you can help GetFreeCourses.Me.txt 182 bytes
19. Learn Python Part 2/4.1 Truthy vs Falsey Stackoverflow.html 170 bytes
5. Data Science Environment Setup/3.1 Getting your computer ready for machine learning How.html 167 bytes
18. Learn Python/5.1 Python 2 vs Python 3.html 161 bytes
2. Machine Learning 101/7. Are You Getting It Yet.html 160 bytes
11. Milestone Project 1 Supervised Learning (Binary Classification)/2.2 Structured Data Projects on GitHub.html 155 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.4 Structured Data Projects on GitHub.html 155 bytes
3. Machine Learning and Data Science Framework/3.1 A 6 Step Field Guide for Machine Learning Modelling (blog post).html 147 bytes
6. Pandas Data Analysis/9.2 Jake VanderPlas_s Data Manipulation with Pandas.html 146 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/9.1 Pandas Categorical Datatype Documentation.html 143 bytes
5. Data Science Environment Setup/3.3 Getting started with Conda (documentation).html 139 bytes
9. Scikit-learn Creating Machine Learning Models/14.1 Scikit-Learn machine learning map (how to choose the right machine learning model).html 133 bytes
6. Pandas Data Analysis/3.4 10-minutes to pandas (from the pandas documentation).html 132 bytes
13. Data Engineering/7.2 OLTP vs OLAP.html 126 bytes
18. Learn Python/43.1 Dictionary Methods.html 119 bytes
7. NumPy/12.1 Matrix Multiplication Explained.html 119 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.2 Kaggle Bluebook for Bulldozers Competition.html 118 bytes
13. Data Engineering/7.1 A Primer on ACID Transactions.html 117 bytes
18. Learn Python/16.1 Python Keywords.html 117 bytes
18. Learn Python/35.2 Python Keywords.html 117 bytes
5. Data Science Environment Setup/10.2 Dataquest Jupyter Notebook for Beginners Tutorial.html 117 bytes
18. Learn Python/18.1 Exercise Repl.html 116 bytes
21. Where To Go From Here/GetFreeCourses.Me.url 116 bytes
7. NumPy/10.1 Standard deviation and variance explained.html 116 bytes
7. NumPy/8.1 Standard deviation and variance explained.html 116 bytes
7. NumPy/9.1 Standard deviation and variance explained.html 116 bytes
GetFreeCourses.Me.url 116 bytes
18. Learn Python/26.2 String Methods.html 115 bytes
18. Learn Python/46.1 Tuple Methods.html 114 bytes
18. Learn Python/34.1 List Methods.html 113 bytes
18. Learn Python/48.1 Sets Methods.html 112 bytes
18. Learn Python/15.1 Base Numbers.html 111 bytes
5. Data Science Environment Setup/10.3 Jupyter Notebook documentation.html 111 bytes
18. Learn Python/26.1 Built in Functions.html 109 bytes
19. Learn Python Part 2/30.1 Solution Repl.html 108 bytes
6. Pandas Data Analysis/13.1 Course notebooks - Github.html 108 bytes
9. Scikit-learn Creating Machine Learning Models/2.2 Scikit-Learn Documentation.html 108 bytes
5. Data Science Environment Setup/5.1 Miniconda download documentation.html 107 bytes
5. Data Science Environment Setup/7.1 Miniconda download documentation.html 107 bytes
18. Learn Python/13.1 Exercise Repl.html 106 bytes
18. Learn Python/14.1 Exercise Repl.html 106 bytes
18. Learn Python/29.1 Python Comments Best Practices.html 106 bytes
6. Pandas Data Analysis/3.1 Pandas Documentation.html 106 bytes
18. Learn Python/10.1 Floating point numbers.html 104 bytes
18. Learn Python/23.1 Exercise Repl.html 104 bytes
18. Learn Python/5.2 The Story of Python.html 104 bytes
8. Matplotlib + Seaborn Plotting and Data Visualization/2.2 Matplotlib Documentation.html 103 bytes
19. Learn Python Part 2/20.1 Solution Repl.html 102 bytes
19. Learn Python Part 2/43.1 Solution Repl.html 102 bytes
18. Learn Python/24.1 Exercise Repl.html 101 bytes
2. Machine Learning 101/3.1 Teachable Machine.html 101 bytes
19. Learn Python Part 2/43.2 Exercise Repl.html 100 bytes
19. Learn Python Part 2/18.1 Solution Repl.html 99 bytes
19. Learn Python Part 2/18.2 Exercise Repl.html 99 bytes
18. Learn Python/44.1 Exercise Repl.html 97 bytes
19. Learn Python Part 2/34.1 Solution Repl.html 95 bytes
6. Pandas Data Analysis/13.2 Google Colab.html 95 bytes
18. Learn Python/35.1 Exercise Repl.html 94 bytes
18. Learn Python/37.1 Exercise Repl.html 94 bytes
18. Learn Python/33.1 Exercise Repl.html 93 bytes
5. Data Science Environment Setup/3.2 Conda documentation.html 93 bytes
13. Data Engineering/2.1 Kaggle.html 92 bytes
18. Learn Python/32.1 Exercise Repl.html 92 bytes
19. Learn Python Part 2/12.1 Solution Repl.html 92 bytes
18. Learn Python/48.2 Exercise Repl.html 91 bytes
2. Machine Learning 101/5.1 Machine Learning Playground.html 88 bytes
7. NumPy/2.1 NumPy Documentation.html 83 bytes
8. Matplotlib + Seaborn Plotting and Data Visualization/Tutnetflix.com - Telegram @FTUplusrip.txt 37 bytes

GetFreeCourses.Me-Udemy-Complete Machine Learning and Data Science Zero to Mastery

File List

Download Torrent

Related Resources

Copyright Infringement