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Machine Learning
Data Exploration & Preparation
Exploration & Preparation
Machine Learning Foundation
Introduction
Training vs Testing
Underfitting-Overfitting
Bias Variance Trade-off
Performance Metrics
Regularization
Feature Selection
Supervised-Unsupervised Learning
Dimensionality Reduction
Regression
Linear Regression
Implementation
Ridge Regression
Lasso Regression
Classification
Logistic Regression
Decision Tree Theory
Decision Tree Implementation
Random Forest
Clustering
Introduction
Centroid Based : K-Means
Connectivity Based : Hierarchical
Density Based : DBSCAN
Time Series
Time Series Analysis
Text Analytics
Introduction
Natural Language Processing Toolkit (NLTK)
Naive Bayes Algorithm
Vectorizers
Movie Sentiment Analysis
Twitter Sentiment Analysis
Support Vector Machine (SVM)
Introduction
Digits Recognition Problem
Face Recognition Problem
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Density Based : DBSCAN
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