Machine Learning with Python

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We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. What is Machine learning Features of Machine Learning Difference between regular program and machine learning program Applications of Machine Learning Types of Machine Learning What is Supervised Learning What is Reinforcement Learning What is Neighbours algorithm K Nearest Neighbours classification K Nearest Neighbours Regression Detailed Supervised Learning Supervised Learning Algorithms Linear Regression Use Case(with Demo)Model Fitting Need for Logistic Regression What is Logistic Regression?Ridge and lasso regression Support vector Machines Pre process of Machine learning data ML Pipeline What is Unsupervised Learning What is Clustering Types of Clustering Tree Based Modeles What is Decision Tree What is Random Forest What is Adaboost What is Gradient boostingstochastic gradient boostinng What is Naïve Bayes Calculation using weather dataset Entropy Calculation using weather dataset Trees Entropy and Gini Maths Introduction Pipeline with Simple Imputer and SVCPipeline with feature selection and SVCDropping Missing Data Regression with categorical features using ridge algorithmprocessing Categorical Features part2processing Categorical Featuresprocessing of machine learning data Delete Outliersprocessing of machine learning data Outliers