Mastering Machine Learning Algorithms using Python | A5F6EB00E39343EB777840E44F2C7EC3147865F0

Mastering Machine Learning Algorithms using Python

Name	Mastering Machine Learning Algorithms using Python	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	7.7 GB
Total Files	243
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/Chapter 13 Introduction to Deep Learning/
001. Introduction to Deep Learning.mp4	262.8 MB
Chapter 01 Introduction to Machine Learning/
001. Course Introduction.mp4	57.6 MB
002. Introduction to Machine Learning.en.srt	17.4 KB
002. Introduction to Machine Learning.mp4	45.6 MB
003. Machine Learning Terminology.en.srt	20.3 KB
003. Machine Learning Terminology.mp4	42.8 MB
004. History of Machine Learning.en.srt	23.1 KB
004. History of Machine Learning.mp4	115.6 MB
005. Machine Learning Use Cases and Types.en.srt	31.1 KB
005. Machine Learning Use Cases and Types.mp4	74.6 MB
006. Role of Data in Machine Learning.en.srt	8.9 KB
006. Role of Data in Machine Learning.mp4	28.2 MB
007. Challenges in Machine Learning.en.srt	27.5 KB
007. Challenges in Machine Learning.mp4	95.0 MB
008. Machine Learning Life Cycle and Pipelines.en.srt	29.4 KB
008. Machine Learning Life Cycle and Pipelines.mp4	80.6 MB
009. Regression Problems.en.srt	15.2 KB
009. Regression Problems.mp4	40.8 MB
010. Regression Models and Performance Metrics.en.srt	17.5 KB
010. Regression Models and Performance Metrics.mp4	54.5 MB
011. Classification Problems and Performance Metrics.en.srt	18.9 KB
011. Classification Problems and Performance Metrics.mp4	51.3 MB
012. Optimizing Classification Metrics.en.srt	13.8 KB
012. Optimizing Classification Metrics.mp4	77.2 MB
013. Bias and Variance.en.srt	13.3 KB
013. Bias and Variance.mp4	37.2 MB
001. Course Introduction.en.srt	22.3 KB
Chapter 02 Statistical Techniques/
001. Statistics and Experiments.en.srt	28.9 KB
001. Statistics and Experiments.mp4	67.0 MB
002. Types of Data and Descriptive Statistics.en.srt	27.9 KB
002. Types of Data and Descriptive Statistics.mp4	68.6 MB
003. Random Variables and Normal Distribution.en.srt	8.6 KB
003. Random Variables and Normal Distribution.mp4	27.2 MB
004. Histograms and Normal Approximation.en.srt	26.7 KB
004. Histograms and Normal Approximation.mp4	93.4 MB
005. Central Limit Theorem.en.srt	24.2 KB
005. Central Limit Theorem.mp4	79.4 MB
006. Probability Theory.en.srt	17.5 KB
006. Probability Theory.mp4	68.0 MB
007. Binomial Theory - Expected Value and Standard Error.en.srt	25.7 KB
007. Binomial Theory - Expected Value and Standard Error.mp4	84.6 MB
008. Hypothesis Testing.en.srt	31.4 KB
008. Hypothesis Testing.mp4	100.4 MB
Chapter 03 Learning Python/
001. Introduction to Python.en.srt	11.1 KB
001. Introduction to Python.mp4	26.8 MB
002. Starting with Python with Jupyter Notebook.en.srt	15.0 KB
002. Starting with Python with Jupyter Notebook.mp4	43.5 MB
003. Python Variables and Conditions.en.srt	33.0 KB
003. Python Variables and Conditions.mp4	88.6 MB
004. Python Iterations 1.en.srt	19.2 KB
004. Python Iterations 1.mp4	49.7 MB
005. Python Iterations 2.en.srt	14.7 KB
005. Python Iterations 2.mp4	39.8 MB
006. Python Lists.en.srt	20.9 KB
006. Python Lists.mp4	80.0 MB
007. Python Tuples.en.srt	24.8 KB
007. Python Tuples.mp4	90.3 MB
008. Python Dictionaries 1.en.srt	20.4 KB
008. Python Dictionaries 1.mp4	86.3 MB
009. Python Dictionaries 2.en.srt	6.9 KB
009. Python Dictionaries 2.mp4	32.8 MB
010. Python Sets 1.en.srt	34.4 KB
010. Python Sets 1.mp4	136.7 MB
011. Python Sets 2.en.srt	2.8 KB
011. Python Sets 2.mp4	10.3 MB
012. Numpy Arrays 1.en.srt	20.0 KB
012. Numpy Arrays 1.mp4	66.7 MB
013. Numpy Arrays 2.en.srt	20.3 KB
013. Numpy Arrays 2.mp4	68.9 MB
014. Numpy Arrays 3.en.srt	18.9 KB
014. Numpy Arrays 3.mp4	55.7 MB
015. Pandas Series 1.en.srt	21.2 KB
015. Pandas Series 1.mp4	73.3 MB
016. Pandas Series 2.en.srt	22.9 KB
016. Pandas Series 2.mp4	98.3 MB
017. Pandas Series 3.en.srt	23.0 KB
017. Pandas Series 3.mp4	83.5 MB
018. Pandas Series 4.en.srt	20.7 KB
018. Pandas Series 4.mp4	76.9 MB
019. Pandas DataFrame 1.en.srt	21.1 KB
019. Pandas DataFrame 1.mp4	64.2 MB
020. Pandas DataFrame 2.en.srt	19.7 KB
020. Pandas DataFrame 2.mp4	61.3 MB
021. Pandas DataFrame 3.en.srt	18.5 KB
021. Pandas DataFrame 3.mp4	72.6 MB
022. Pandas DataFrame 4.en.srt	18.9 KB
022. Pandas DataFrame 4.mp4	60.4 MB
023. Pandas DataFrame 5.en.srt	28.9 KB
023. Pandas DataFrame 5.mp4	126.1 MB
024. Pandas DataFrame 6.en.srt	20.6 KB
024. Pandas DataFrame 6.mp4	70.3 MB
025. Python User Defined Functions.en.srt	20.9 KB
025. Python User Defined Functions.mp4	52.7 MB
026. Python Lambda Functions.en.srt	27.7 KB
026. Python Lambda Functions.mp4	82.2 MB
027. Python Lambda Functions and Date-Time Operations.en.srt	25.0 KB
027. Python Lambda Functions and Date-Time Operations.mp4	66.7 MB
028. Python String Operations.en.srt	18.1 KB
028. Python String Operations.mp4	46.9 MB
Chapter 04 Exploratory Data Analysis/
001. Exploratory Data Analysis.en.srt	23.4 KB
001. Exploratory Data Analysis.mp4	57.6 MB
002. Tools and Processes of EDA.en.srt	24.2 KB
002. Tools and Processes of EDA.mp4	70.6 MB
003. EDA Project 1.en.srt	23.5 KB
003. EDA Project 1.mp4	83.6 MB
004. EDA Project 2.en.srt	21.4 KB
004. EDA Project 2.mp4	64.0 MB
005. EDA Project 3.en.srt	13.7 KB
005. EDA Project 3.mp4	31.1 MB
006. EDA Project 4.en.srt	26.7 KB
006. EDA Project 4.mp4	68.2 MB
007. EDA Project 5.en.srt	22.2 KB
007. EDA Project 5.mp4	75.5 MB
008. EDA Project 6.en.srt	25.8 KB
008. EDA Project 6.mp4	81.6 MB
009. EDA Project 7.en.srt	38.6 KB
009. EDA Project 7.mp4	138.3 MB
Chapter 05 Linear Regression/
001. Linear Regression Introduction.en.srt	27.7 KB
001. Linear Regression Introduction.mp4	54.1 MB
002. Training and Cost Function.en.srt	35.6 KB
002. Training and Cost Function.mp4	84.4 MB
003. Cost Functions and Gradient Descent.en.srt	19.0 KB
003. Cost Functions and Gradient Descent.mp4	71.5 MB
004. Linear Regression - Practical Approach.en.srt	23.6 KB
004. Linear Regression - Practical Approach.mp4	61.0 MB
005. Feature Scaling and Cost Functions.en.srt	17.9 KB
005. Feature Scaling and Cost Functions.mp4	55.9 MB
006. OLS Assumptions and Testing.en.srt	26.7 KB
006. OLS Assumptions and Testing.mp4	91.4 MB
007. Car Price Prediction.en.srt	20.7 KB
007. Car Price Prediction.mp4	75.4 MB
008. Data Preparation and Analysis 1.en.srt	19.3 KB
008. Data Preparation and Analysis 1.mp4	50.7 MB
009. Data Preparation and Analysis 2.en.srt	21.5 KB
009. Data Preparation and Analysis 2.mp4	57.5 MB
010. Data Preparation and Analysis 3.en.srt	26.5 KB
010. Data Preparation and Analysis 3.mp4	104.6 MB
011. Model Building.en.srt	23.0 KB
011. Model Building.mp4	86.6 MB
012. Model Evaluation and Optimization.en.srt	20.9 KB
012. Model Evaluation and Optimization.mp4	79.2 MB
013. Model Optimization.en.srt	4.7 KB
013. Model Optimization.mp4	14.1 MB
Chapter 06 Logistic Regression/
001. Logistic Regression Introduction.en.srt	21.0 KB
001. Logistic Regression Introduction.mp4	80.9 MB
002. Logit Model.en.srt	35.6 KB
002. Logit Model.mp4	96.7 MB
003. Telecom Churn Case Study.en.srt	25.6 KB
003. Telecom Churn Case Study.mp4	82.2 MB
004. Data Analysis and Feature Engineering.en.srt	33.4 KB
004. Data Analysis and Feature Engineering.mp4	108.3 MB
005. Build the Logistic Model.en.srt	18.1 KB
005. Build the Logistic Model.mp4	85.2 MB
006. Model Evaluation - AUC-ROC.en.srt	33.9 KB
006. Model Evaluation - AUC-ROC.mp4	127.3 MB
007. Model Optimization 1.en.srt	21.5 KB
007. Model Optimization 1.mp4	70.7 MB
008. Model Optimization 2.en.srt	19.5 KB
008. Model Optimization 2.mp4	64.8 MB
Chapter 07 Naive Bayes Classification Algorithm/
001. Naive Bayes Probability Model.en.srt	21.6 KB
001. Naive Bayes Probability Model.mp4	63.8 MB
002. Naive Bayes Probability Computation.en.srt	22.5 KB
002. Naive Bayes Probability Computation.mp4	71.6 MB
003. Employee Attrition Case Study.en.srt	24.3 KB
003. Employee Attrition Case Study.mp4	75.1 MB
004. Model Building and Optimization.en.srt	22.0 KB
004. Model Building and Optimization.mp4	58.0 MB
Chapter 08 Decision Tree Classifier/
001. Decision Tree - Model Concept.en.srt	22.7 KB
001. Decision Tree - Model Concept.mp4	55.1 MB
002. Decision Tree - Learning Steps.en.srt	28.3 KB
002. Decision Tree - Learning Steps.mp4	86.0 MB
003. Gini Index and Entropy Measures.en.srt	22.4 KB
003. Gini Index and Entropy Measures.mp4	64.1 MB
004. Pruning and Hyperparameter Tuning.en.srt	15.4 KB
004. Pruning and Hyperparameter Tuning.mp4	50.6 MB
005. Iris Dataset Case Study.en.srt	25.3 KB
005. Iris Dataset Case Study.mp4	73.7 MB
006. Model Optimization using Grid Search Cross Validation.en.srt	22.6 KB
006. Model Optimization using Grid Search Cross Validation.mp4	89.7 MB
Chapter 09 Random Forest Ensemble/
001. Ensemble Techniques Bagging and Random Forest.en.srt	25.7 KB
001. Ensemble Techniques Bagging and Random Forest.mp4	62.6 MB
002. Random Forest Steps Pruning and Optimization.en.srt	30.4 KB
002. Random Forest Steps Pruning and Optimization.mp4	81.3 MB
003. Model Building and Hyperparameter Tuning using Grid Search CV.en.srt	26.3 KB
003. Model Building and Hyperparameter Tuning using Grid Search CV.mp4	92.2 MB
004. Optimization Continued.en.srt	13.6 KB
004. Optimization Continued.mp4	55.8 MB
Chapter 10 Support Vector Machine/
001. Support Vector Machine Concepts.en.srt	27.4 KB
001. Support Vector Machine Concepts.mp4	74.0 MB
002. Support Vector Machine Metrics and Polynomial SVM.en.srt	19.9 KB
002. Support Vector Machine Metrics and Polynomial SVM.mp4	66.5 MB
003. Support Vector Machine Project 1.en.srt	19.1 KB
003. Support Vector Machine Project 1.mp4	50.7 MB
004. Support Vector Machine Predictions.en.srt	6.0 KB
004. Support Vector Machine Predictions.mp4	22.8 MB
005. Support Vector Machine - Classifying Polynomial Data.en.srt	13.5 KB
005. Support Vector Machine - Classifying Polynomial Data.mp4	45.0 MB
Chapter 11 Dimensionality Reduction - Principal Component Analysis (PCA)/
001. Principal Component Analysis - Concepts.en.srt	26.1 KB
001. Principal Component Analysis - Concepts.mp4	90.0 MB
002. Principal Component Analysis - Computations 1.en.srt	30.0 KB
002. Principal Component Analysis - Computations 1.mp4	67.9 MB
003. Principal Component Analysis - Computations 2.en.srt	18.2 KB
003. Principal Component Analysis - Computations 2.mp4	49.0 MB
004. Principal Component Analysis Practicals.en.srt	20.8 KB
004. Principal Component Analysis Practicals.mp4	60.8 MB
Chapter 12 Unsupervised Learning using K-Means Clustering/
001. Unsupervised Learning - K-Mean Clustering.en.srt	22.7 KB
001. Unsupervised Learning - K-Mean Clustering.mp4	67.9 MB
002. K-Means Clustering Computation.en.srt	41.8 KB
002. K-Means Clustering Computation.mp4	120.4 MB
003. K-Means Clustering Optimization.en.srt	12.6 KB
003. K-Means Clustering Optimization.mp4	32.3 MB
004. K-Means - Data Preparation and Modelling.en.srt	23.9 KB
004. K-Means - Data Preparation and Modelling.mp4	68.9 MB
005. K-Means - Model Optimization.en.srt	19.6 KB
005. K-Means - Model Optimization.mp4	55.8 MB
Chapter 13 Introduction to Deep Learning/
001. Introduction to Deep Learning.en.srt	106.1 KB
z.Mastering-Machine-Learning-Algorithms-using-Python-main/
README.md	0.1 KB
/.../Code-and-Data-Files/
Car_sales.csv	11.9 KB
Car_sales.xls	72.2 KB
CarPrice_Assignment.csv	26.5 KB
Car-price-prediction-linear-regression-Intro-version.ipynb	237.2 KB
churn_data.csv	484.4 KB
credit-card-default.csv	2.9 MB
customer_data.csv	181.6 KB
customer-segmentation-k-means-analysis.ipynb	560.4 KB
Decision_Tree_IRIS.ipynb	467.1 KB
EDA-Overview-Lending-Club.ipynb	354.9 KB
Employee-Attrition-using-Naive-Bayes.ipynb	47.6 KB
Fashion_MNIST_Image_Classification_using_Deep_Learning_tf_Keras.ipynb	12.8 KB
gapminderData.csv	82.1 KB
Handwritten-Digit-MNIST-SVM.ipynb	112.9 KB
HR-Employee-Attrition.csv	226.5 KB
internet_data.csv	459.4 KB
iris_csv.csv	4.6 KB
Lending-Club-EDA-Project.ipynb	816.2 KB
loan.csv	32.8 MB
Machine-Learning-Foundations.ipynb	828.5 KB
Mall_Customers.csv	3.8 KB
newhousing.csv	32.3 KB
PCA-Housing.ipynb	70.6 KB
Python-Intro-Numpy-Pandas.ipynb	689.3 KB
Random-Forest-Credit-Default-Prediction.ipynb	208.8 KB
telecom-churn-prediction-logistic-regression.ipynb	801.0 KB
Total files 243