Mastering Machine Learning Algorithms using Python

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Last Access Time	Oct. 21, 2025, 4:01 a.m.
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Keywords	Python Machine Algorithms Learning Mastering using
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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

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