Mastering Machine Learning Algorithms using Python

Creation Time	Aug. 27, 2024, 12:47 p.m.
Last Access Time	March 21, 2026, 8:16 a.m.
File Size	7.2 GB
Keywords	Python Machine Algorithms Learning Mastering using
Total Requests	1343
Total Files	243
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

Chapter 13 Introduction to Deep Learning/001. Introduction to Deep Learning.mp4 250.7 MB
Chapter 04 Exploratory Data Analysis/009. EDA Project 7.mp4 131.9 MB
Chapter 03 Learning Python/010. Python Sets 1.mp4 130.4 MB
Chapter 06 Logistic Regression/006. Model Evaluation - AUC-ROC.mp4 121.4 MB
Chapter 03 Learning Python/023. Pandas DataFrame 5.mp4 120.3 MB
Chapter 12 Unsupervised Learning using K-Means Clustering/002. K-Means Clustering Computation.mp4 114.9 MB
Chapter 01 Introduction to Machine Learning/004. History of Machine Learning.mp4 110.2 MB
Chapter 06 Logistic Regression/004. Data Analysis and Feature Engineering.mp4 103.3 MB
Chapter 05 Linear Regression/010. Data Preparation and Analysis 3.mp4 99.7 MB
Chapter 02 Statistical Techniques/008. Hypothesis Testing.mp4 95.8 MB
Chapter 03 Learning Python/016. Pandas Series 2.mp4 93.7 MB
Chapter 06 Logistic Regression/002. Logit Model.mp4 92.2 MB
Chapter 01 Introduction to Machine Learning/007. Challenges in Machine Learning.mp4 90.6 MB
Chapter 02 Statistical Techniques/004. Histograms and Normal Approximation.mp4 89.1 MB
Chapter 09 Random Forest Ensemble/003. Model Building and Hyperparameter Tuning using Grid Search CV.mp4 87.9 MB
Chapter 05 Linear Regression/006. OLS Assumptions and Testing.mp4 87.2 MB
Chapter 03 Learning Python/007. Python Tuples.mp4 86.1 MB
Chapter 11 Dimensionality Reduction - Principal Component Analysis (PCA)/001. Principal Component Analysis - Concepts.mp4 85.8 MB
Chapter 08 Decision Tree Classifier/006. Model Optimization using Grid Search Cross Validation.mp4 85.5 MB
Chapter 03 Learning Python/003. Python Variables and Conditions.mp4 84.5 MB
Chapter 05 Linear Regression/011. Model Building.mp4 82.6 MB
Chapter 03 Learning Python/008. Python Dictionaries 1.mp4 82.3 MB
Chapter 08 Decision Tree Classifier/002. Decision Tree - Learning Steps.mp4 82.0 MB
Chapter 06 Logistic Regression/005. Build the Logistic Model.mp4 81.2 MB
Chapter 02 Statistical Techniques/007. Binomial Theory - Expected Value and Standard Error.mp4 80.6 MB
Chapter 05 Linear Regression/002. Training and Cost Function.mp4 80.5 MB
Chapter 04 Exploratory Data Analysis/003. EDA Project 1.mp4 79.7 MB
Chapter 03 Learning Python/017. Pandas Series 3.mp4 79.6 MB
Chapter 06 Logistic Regression/003. Telecom Churn Case Study.mp4 78.4 MB
Chapter 03 Learning Python/026. Python Lambda Functions.mp4 78.4 MB
Chapter 04 Exploratory Data Analysis/008. EDA Project 6.mp4 77.9 MB
Chapter 09 Random Forest Ensemble/002. Random Forest Steps Pruning and Optimization.mp4 77.5 MB
Chapter 06 Logistic Regression/001. Logistic Regression Introduction.mp4 77.2 MB
Chapter 01 Introduction to Machine Learning/008. Machine Learning Life Cycle and Pipelines.mp4 76.8 MB
Chapter 03 Learning Python/006. Python Lists.mp4 76.3 MB
Chapter 02 Statistical Techniques/005. Central Limit Theorem.mp4 75.7 MB
Chapter 05 Linear Regression/012. Model Evaluation and Optimization.mp4 75.5 MB
Chapter 01 Introduction to Machine Learning/012. Optimizing Classification Metrics.mp4 73.6 MB
Chapter 03 Learning Python/018. Pandas Series 4.mp4 73.3 MB
Chapter 04 Exploratory Data Analysis/007. EDA Project 5.mp4 72.0 MB
Chapter 05 Linear Regression/007. Car Price Prediction.mp4 71.9 MB
Chapter 07 Naive Bayes Classification Algorithm/003. Employee Attrition Case Study.mp4 71.6 MB
Chapter 01 Introduction to Machine Learning/005. Machine Learning Use Cases and Types.mp4 71.1 MB
Chapter 10 Support Vector Machine/001. Support Vector Machine Concepts.mp4 70.5 MB
Chapter 08 Decision Tree Classifier/005. Iris Dataset Case Study.mp4 70.3 MB
Chapter 03 Learning Python/015. Pandas Series 1.mp4 69.9 MB
Chapter 03 Learning Python/021. Pandas DataFrame 3.mp4 69.3 MB
Chapter 07 Naive Bayes Classification Algorithm/002. Naive Bayes Probability Computation.mp4 68.3 MB
Chapter 05 Linear Regression/003. Cost Functions and Gradient Descent.mp4 68.2 MB
Chapter 06 Logistic Regression/007. Model Optimization 1.mp4 67.4 MB
Chapter 04 Exploratory Data Analysis/002. Tools and Processes of EDA.mp4 67.4 MB
Chapter 03 Learning Python/024. Pandas DataFrame 6.mp4 67.0 MB
Chapter 03 Learning Python/013. Numpy Arrays 2.mp4 65.7 MB
Chapter 12 Unsupervised Learning using K-Means Clustering/004. K-Means - Data Preparation and Modelling.mp4 65.7 MB
Chapter 02 Statistical Techniques/002. Types of Data and Descriptive Statistics.mp4 65.4 MB
Chapter 04 Exploratory Data Analysis/006. EDA Project 4.mp4 65.0 MB
Chapter 02 Statistical Techniques/006. Probability Theory.mp4 64.8 MB
Chapter 12 Unsupervised Learning using K-Means Clustering/001. Unsupervised Learning - K-Mean Clustering.mp4 64.8 MB
Chapter 11 Dimensionality Reduction - Principal Component Analysis (PCA)/002. Principal Component Analysis - Computations 1.mp4 64.7 MB
Chapter 02 Statistical Techniques/001. Statistics and Experiments.mp4 63.9 MB
Chapter 03 Learning Python/012. Numpy Arrays 1.mp4 63.6 MB
Chapter 03 Learning Python/027. Python Lambda Functions and Date-Time Operations.mp4 63.6 MB
Chapter 10 Support Vector Machine/002. Support Vector Machine Metrics and Polynomial SVM.mp4 63.4 MB
Chapter 06 Logistic Regression/008. Model Optimization 2.mp4 61.8 MB
Chapter 03 Learning Python/019. Pandas DataFrame 1.mp4 61.3 MB
Chapter 08 Decision Tree Classifier/003. Gini Index and Entropy Measures.mp4 61.1 MB
Chapter 04 Exploratory Data Analysis/004. EDA Project 2.mp4 61.0 MB
Chapter 07 Naive Bayes Classification Algorithm/001. Naive Bayes Probability Model.mp4 60.9 MB
Chapter 09 Random Forest Ensemble/001. Ensemble Techniques Bagging and Random Forest.mp4 59.7 MB
Chapter 03 Learning Python/020. Pandas DataFrame 2.mp4 58.5 MB
Chapter 05 Linear Regression/004. Linear Regression - Practical Approach.mp4 58.2 MB
Chapter 11 Dimensionality Reduction - Principal Component Analysis (PCA)/004. Principal Component Analysis Practicals.mp4 58.0 MB
Chapter 03 Learning Python/022. Pandas DataFrame 4.mp4 57.6 MB
Chapter 07 Naive Bayes Classification Algorithm/004. Model Building and Optimization.mp4 55.3 MB
Chapter 01 Introduction to Machine Learning/001. Course Introduction.mp4 54.9 MB
Chapter 04 Exploratory Data Analysis/001. Exploratory Data Analysis.mp4 54.9 MB
Chapter 05 Linear Regression/009. Data Preparation and Analysis 2.mp4 54.8 MB
Chapter 05 Linear Regression/005. Feature Scaling and Cost Functions.mp4 53.3 MB
Chapter 12 Unsupervised Learning using K-Means Clustering/005. K-Means - Model Optimization.mp4 53.3 MB
Chapter 09 Random Forest Ensemble/004. Optimization Continued.mp4 53.2 MB
Chapter 03 Learning Python/014. Numpy Arrays 3.mp4 53.1 MB
Chapter 08 Decision Tree Classifier/001. Decision Tree - Model Concept.mp4 52.5 MB
Chapter 01 Introduction to Machine Learning/010. Regression Models and Performance Metrics.mp4 51.9 MB
Chapter 05 Linear Regression/001. Linear Regression Introduction.mp4 51.6 MB
Chapter 03 Learning Python/025. Python User Defined Functions.mp4 50.2 MB
Chapter 01 Introduction to Machine Learning/011. Classification Problems and Performance Metrics.mp4 48.9 MB
Chapter 05 Linear Regression/008. Data Preparation and Analysis 1.mp4 48.4 MB
Chapter 10 Support Vector Machine/003. Support Vector Machine Project 1.mp4 48.4 MB
Chapter 08 Decision Tree Classifier/004. Pruning and Hyperparameter Tuning.mp4 48.3 MB
Chapter 03 Learning Python/004. Python Iterations 1.mp4 47.4 MB
Chapter 11 Dimensionality Reduction - Principal Component Analysis (PCA)/003. Principal Component Analysis - Computations 2.mp4 46.7 MB
Chapter 03 Learning Python/028. Python String Operations.mp4 44.7 MB
Chapter 01 Introduction to Machine Learning/002. Introduction to Machine Learning.mp4 43.5 MB
Chapter 10 Support Vector Machine/005. Support Vector Machine - Classifying Polynomial Data.mp4 42.9 MB
Chapter 03 Learning Python/002. Starting with Python with Jupyter Notebook.mp4 41.5 MB
Chapter 01 Introduction to Machine Learning/003. Machine Learning Terminology.mp4 40.8 MB
Chapter 01 Introduction to Machine Learning/009. Regression Problems.mp4 38.9 MB
Chapter 03 Learning Python/005. Python Iterations 2.mp4 38.0 MB
Chapter 01 Introduction to Machine Learning/013. Bias and Variance.mp4 35.4 MB
Chapter 03 Learning Python/009. Python Dictionaries 2.mp4 31.3 MB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/loan.csv 31.3 MB
Chapter 12 Unsupervised Learning using K-Means Clustering/003. K-Means Clustering Optimization.mp4 30.8 MB
Chapter 04 Exploratory Data Analysis/005. EDA Project 3.mp4 29.7 MB
Chapter 01 Introduction to Machine Learning/006. Role of Data in Machine Learning.mp4 26.9 MB
Chapter 02 Statistical Techniques/003. Random Variables and Normal Distribution.mp4 25.9 MB
Chapter 03 Learning Python/001. Introduction to Python.mp4 25.5 MB
Chapter 10 Support Vector Machine/004. Support Vector Machine Predictions.mp4 21.8 MB
Chapter 05 Linear Regression/013. Model Optimization.mp4 13.5 MB
Chapter 03 Learning Python/011. Python Sets 2.mp4 9.8 MB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/credit-card-default.csv 2.7 MB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Machine-Learning-Foundations.ipynb 809.1 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Lending-Club-EDA-Project.ipynb 797.1 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/telecom-churn-prediction-logistic-regression.ipynb 782.2 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Python-Intro-Numpy-Pandas.ipynb 673.2 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/customer-segmentation-k-means-analysis.ipynb 547.3 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/churn_data.csv 473.1 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Decision_Tree_IRIS.ipynb 456.2 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/internet_data.csv 448.7 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/EDA-Overview-Lending-Club.ipynb 346.6 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Car-price-prediction-linear-regression-Intro-version.ipynb 231.7 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/HR-Employee-Attrition.csv 221.2 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Random-Forest-Credit-Default-Prediction.ipynb 203.9 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/customer_data.csv 177.3 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Handwritten-Digit-MNIST-SVM.ipynb 110.2 KB
Chapter 13 Introduction to Deep Learning/001. Introduction to Deep Learning.en.srt 103.6 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/gapminderData.csv 80.2 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Car_sales.xls 70.5 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/PCA-Housing.ipynb 69.0 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Employee-Attrition-using-Naive-Bayes.ipynb 46.5 KB
Chapter 12 Unsupervised Learning using K-Means Clustering/002. K-Means Clustering Computation.en.srt 40.8 KB
Chapter 04 Exploratory Data Analysis/009. EDA Project 7.en.srt 37.7 KB
Chapter 05 Linear Regression/002. Training and Cost Function.en.srt 34.8 KB
Chapter 06 Logistic Regression/002. Logit Model.en.srt 34.8 KB
Chapter 03 Learning Python/010. Python Sets 1.en.srt 33.6 KB
Chapter 06 Logistic Regression/006. Model Evaluation - AUC-ROC.en.srt 33.1 KB
Chapter 06 Logistic Regression/004. Data Analysis and Feature Engineering.en.srt 32.7 KB
Chapter 03 Learning Python/003. Python Variables and Conditions.en.srt 32.2 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/newhousing.csv 31.5 KB
Chapter 02 Statistical Techniques/008. Hypothesis Testing.en.srt 30.7 KB
Chapter 01 Introduction to Machine Learning/005. Machine Learning Use Cases and Types.en.srt 30.4 KB
Chapter 09 Random Forest Ensemble/002. Random Forest Steps Pruning and Optimization.en.srt 29.7 KB
Chapter 11 Dimensionality Reduction - Principal Component Analysis (PCA)/002. Principal Component Analysis - Computations 1.en.srt 29.3 KB
Chapter 01 Introduction to Machine Learning/008. Machine Learning Life Cycle and Pipelines.en.srt 28.8 KB
Chapter 02 Statistical Techniques/001. Statistics and Experiments.en.srt 28.2 KB
Chapter 03 Learning Python/023. Pandas DataFrame 5.en.srt 28.2 KB
Chapter 08 Decision Tree Classifier/002. Decision Tree - Learning Steps.en.srt 27.7 KB
Chapter 02 Statistical Techniques/002. Types of Data and Descriptive Statistics.en.srt 27.2 KB
Chapter 03 Learning Python/026. Python Lambda Functions.en.srt 27.1 KB
Chapter 05 Linear Regression/001. Linear Regression Introduction.en.srt 27.0 KB
Chapter 01 Introduction to Machine Learning/007. Challenges in Machine Learning.en.srt 26.9 KB
Chapter 10 Support Vector Machine/001. Support Vector Machine Concepts.en.srt 26.8 KB
Chapter 05 Linear Regression/006. OLS Assumptions and Testing.en.srt 26.1 KB
Chapter 02 Statistical Techniques/004. Histograms and Normal Approximation.en.srt 26.1 KB
Chapter 04 Exploratory Data Analysis/006. EDA Project 4.en.srt 26.0 KB
Chapter 05 Linear Regression/010. Data Preparation and Analysis 3.en.srt 25.9 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/CarPrice_Assignment.csv 25.9 KB
Chapter 09 Random Forest Ensemble/003. Model Building and Hyperparameter Tuning using Grid Search CV.en.srt 25.7 KB
Chapter 11 Dimensionality Reduction - Principal Component Analysis (PCA)/001. Principal Component Analysis - Concepts.en.srt 25.5 KB
Chapter 04 Exploratory Data Analysis/008. EDA Project 6.en.srt 25.2 KB
Chapter 02 Statistical Techniques/007. Binomial Theory - Expected Value and Standard Error.en.srt 25.1 KB
Chapter 09 Random Forest Ensemble/001. Ensemble Techniques Bagging and Random Forest.en.srt 25.1 KB
Chapter 06 Logistic Regression/003. Telecom Churn Case Study.en.srt 25.0 KB
Chapter 08 Decision Tree Classifier/005. Iris Dataset Case Study.en.srt 24.7 KB
Chapter 03 Learning Python/027. Python Lambda Functions and Date-Time Operations.en.srt 24.4 KB
Chapter 03 Learning Python/007. Python Tuples.en.srt 24.2 KB
Chapter 07 Naive Bayes Classification Algorithm/003. Employee Attrition Case Study.en.srt 23.8 KB
Chapter 04 Exploratory Data Analysis/002. Tools and Processes of EDA.en.srt 23.7 KB
Chapter 02 Statistical Techniques/005. Central Limit Theorem.en.srt 23.6 KB
Chapter 12 Unsupervised Learning using K-Means Clustering/004. K-Means - Data Preparation and Modelling.en.srt 23.3 KB
Chapter 05 Linear Regression/004. Linear Regression - Practical Approach.en.srt 23.0 KB
Chapter 04 Exploratory Data Analysis/003. EDA Project 1.en.srt 22.9 KB
Chapter 04 Exploratory Data Analysis/001. Exploratory Data Analysis.en.srt 22.9 KB
Chapter 01 Introduction to Machine Learning/004. History of Machine Learning.en.srt 22.5 KB
Chapter 05 Linear Regression/011. Model Building.en.srt 22.5 KB
Chapter 03 Learning Python/017. Pandas Series 3.en.srt 22.5 KB
Chapter 03 Learning Python/016. Pandas Series 2.en.srt 22.4 KB
Chapter 08 Decision Tree Classifier/001. Decision Tree - Model Concept.en.srt 22.1 KB
Chapter 12 Unsupervised Learning using K-Means Clustering/001. Unsupervised Learning - K-Mean Clustering.en.srt 22.1 KB
Chapter 08 Decision Tree Classifier/006. Model Optimization using Grid Search Cross Validation.en.srt 22.1 KB
Chapter 07 Naive Bayes Classification Algorithm/002. Naive Bayes Probability Computation.en.srt 21.9 KB
Chapter 08 Decision Tree Classifier/003. Gini Index and Entropy Measures.en.srt 21.8 KB
Chapter 01 Introduction to Machine Learning/001. Course Introduction.en.srt 21.7 KB
Chapter 04 Exploratory Data Analysis/007. EDA Project 5.en.srt 21.6 KB
Chapter 07 Naive Bayes Classification Algorithm/004. Model Building and Optimization.en.srt 21.5 KB
Chapter 07 Naive Bayes Classification Algorithm/001. Naive Bayes Probability Model.en.srt 21.1 KB
Chapter 06 Logistic Regression/007. Model Optimization 1.en.srt 21.0 KB
Chapter 05 Linear Regression/009. Data Preparation and Analysis 2.en.srt 21.0 KB
Chapter 04 Exploratory Data Analysis/004. EDA Project 2.en.srt 20.9 KB
Chapter 03 Learning Python/015. Pandas Series 1.en.srt 20.7 KB
Chapter 03 Learning Python/019. Pandas DataFrame 1.en.srt 20.6 KB
Chapter 06 Logistic Regression/001. Logistic Regression Introduction.en.srt 20.5 KB
Chapter 03 Learning Python/006. Python Lists.en.srt 20.5 KB
Chapter 05 Linear Regression/012. Model Evaluation and Optimization.en.srt 20.4 KB
Chapter 03 Learning Python/025. Python User Defined Functions.en.srt 20.4 KB
Chapter 11 Dimensionality Reduction - Principal Component Analysis (PCA)/004. Principal Component Analysis Practicals.en.srt 20.3 KB
Chapter 05 Linear Regression/007. Car Price Prediction.en.srt 20.2 KB
Chapter 03 Learning Python/018. Pandas Series 4.en.srt 20.2 KB
Chapter 03 Learning Python/024. Pandas DataFrame 6.en.srt 20.2 KB
Chapter 03 Learning Python/008. Python Dictionaries 1.en.srt 20.0 KB
Chapter 03 Learning Python/013. Numpy Arrays 2.en.srt 19.8 KB
Chapter 01 Introduction to Machine Learning/003. Machine Learning Terminology.en.srt 19.8 KB
Chapter 03 Learning Python/012. Numpy Arrays 1.en.srt 19.5 KB
Chapter 10 Support Vector Machine/002. Support Vector Machine Metrics and Polynomial SVM.en.srt 19.4 KB
Chapter 03 Learning Python/020. Pandas DataFrame 2.en.srt 19.2 KB
Chapter 12 Unsupervised Learning using K-Means Clustering/005. K-Means - Model Optimization.en.srt 19.1 KB
Chapter 06 Logistic Regression/008. Model Optimization 2.en.srt 19.0 KB
Chapter 05 Linear Regression/008. Data Preparation and Analysis 1.en.srt 18.8 KB
Chapter 03 Learning Python/004. Python Iterations 1.en.srt 18.8 KB
Chapter 10 Support Vector Machine/003. Support Vector Machine Project 1.en.srt 18.7 KB
Chapter 05 Linear Regression/003. Cost Functions and Gradient Descent.en.srt 18.5 KB
Chapter 01 Introduction to Machine Learning/011. Classification Problems and Performance Metrics.en.srt 18.5 KB
Chapter 03 Learning Python/014. Numpy Arrays 3.en.srt 18.5 KB
Chapter 03 Learning Python/022. Pandas DataFrame 4.en.srt 18.5 KB
Chapter 03 Learning Python/021. Pandas DataFrame 3.en.srt 18.0 KB
Chapter 11 Dimensionality Reduction - Principal Component Analysis (PCA)/003. Principal Component Analysis - Computations 2.en.srt 17.7 KB
Chapter 03 Learning Python/028. Python String Operations.en.srt 17.7 KB
Chapter 06 Logistic Regression/005. Build the Logistic Model.en.srt 17.7 KB
Chapter 05 Linear Regression/005. Feature Scaling and Cost Functions.en.srt 17.5 KB
Chapter 02 Statistical Techniques/006. Probability Theory.en.srt 17.1 KB
Chapter 01 Introduction to Machine Learning/010. Regression Models and Performance Metrics.en.srt 17.1 KB
Chapter 01 Introduction to Machine Learning/002. Introduction to Machine Learning.en.srt 17.0 KB
Chapter 08 Decision Tree Classifier/004. Pruning and Hyperparameter Tuning.en.srt 15.0 KB
Chapter 01 Introduction to Machine Learning/009. Regression Problems.en.srt 14.9 KB
Chapter 03 Learning Python/002. Starting with Python with Jupyter Notebook.en.srt 14.6 KB
Chapter 03 Learning Python/005. Python Iterations 2.en.srt 14.3 KB
Chapter 01 Introduction to Machine Learning/012. Optimizing Classification Metrics.en.srt 13.5 KB
Chapter 04 Exploratory Data Analysis/005. EDA Project 3.en.srt 13.4 KB
Chapter 09 Random Forest Ensemble/004. Optimization Continued.en.srt 13.3 KB
Chapter 10 Support Vector Machine/005. Support Vector Machine - Classifying Polynomial Data.en.srt 13.1 KB
Chapter 01 Introduction to Machine Learning/013. Bias and Variance.en.srt 12.9 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Fashion_MNIST_Image_Classification_using_Deep_Learning_tf_Keras.ipynb 12.5 KB
Chapter 12 Unsupervised Learning using K-Means Clustering/003. K-Means Clustering Optimization.en.srt 12.3 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Car_sales.csv 11.6 KB
Chapter 03 Learning Python/001. Introduction to Python.en.srt 10.8 KB
Chapter 01 Introduction to Machine Learning/006. Role of Data in Machine Learning.en.srt 8.7 KB
Chapter 02 Statistical Techniques/003. Random Variables and Normal Distribution.en.srt 8.4 KB
Chapter 03 Learning Python/009. Python Dictionaries 2.en.srt 6.7 KB
Chapter 10 Support Vector Machine/004. Support Vector Machine Predictions.en.srt 5.8 KB
Chapter 05 Linear Regression/013. Model Optimization.en.srt 4.6 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/iris_csv.csv 4.5 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/Code-and-Data-Files/Mall_Customers.csv 3.7 KB
Chapter 03 Learning Python/011. Python Sets 2.en.srt 2.7 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/README.md 52 bytes

Mastering Machine Learning Algorithms using Python

File List

Download Torrent

Related Resources

Copyright Infringement