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Step-by-Step Machine Learning with Python
Getting Started with Python and Machine Learning
The Course Overview
Introduction to Machine Learning
Installing Software and Setting Up
Exploring the 20 Newsgroups Dataset with Text Analysis Algorithms
Understanding NLP
Touring Powerful NLP Libraries in Python
Getting the Newsgroups Data
Thinking about Features
Visualization
Data Preprocessing
Clustering
Topic Modeling
Spam Email Detection with Naïve Bayes
Getting Started with Classification
Exploring Naïve Bayes
The Mechanics of Naïve Bayes
The Naïve Bayes Implementation
Classifier Performance Evaluation
Model Tuning and cross-validation
News Topic Classification with Support Vector Machine
Recap and Inverse Document Frequency
The Mechanics of SVM
The Implementations of SVM
The Kernels of SVM
Choosing Between the Linear and the RBF Kernel
News topic Classification with Support Vector Machine
Fetal State Classification with SVM
Click-Through Prediction with Tree-Based Algorithms
Brief Overview of Advertising Click-Through Prediction
Decision Tree Classifier
The Implementations of Decision Tree
Click-Through Prediction with Decision Tree
Random Forest - Feature Bagging of Decision Tree
Click-Through Prediction with Logistic Regression
One-Hot Encoding - Converting Categorical Features to Numerical
Logistic Regression Classifier
Click-Through Prediction with Logistic Regression by Gradient Descent
Feature Selection via Random Forest
Stock Price Prediction with Regression Algorithms
Brief Overview of the Stock Market And Stock Price
Predicting Stock Price with Regression Algorithms
Data Acquisition and Feature Generation
Linear Regression
Decision Tree Regression
Support Vector Regression
Regression Performance Evaluation
Stock Price Prediction with Regression Algorithms
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Recap and Inverse Document Frequency
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