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practical-machine-learning-with-python's Introduction

Practical-Machine-Learning-with-Python

Machine Learning tutorials in Python

  1. Part - 1 [ Theory ][ Code ]
  • What is Machine Learning and Types of Machine Learning?
  • Linear Regression
  • Gradient Descent
  • Logistic Regression
  • Overfitting and Underfitting
  • Regularization
  • Cross Validation
  1. Part - 2 [ Theory and Code ]
  • Naive Bayes
  • Support Vector Machines
  • Decision Tree
  • Random Forest and Boosting algorithms
  • Preprocessing and Feature Extraction techniques
  1. Part - 3 [ Theory and Code ]
  • K-nearest Neighbors Algorithm
  • K-means Clustering
  • Principal Component Analysis
  • Neural Networks
  1. Part - 4
  • Project - 1
  1. Part - 5
  • Convolutional Neural Networks
  • Recurrent Neural Networks
  1. Part - 7
  • Autoencoder
  • Denoising Autoencoder
  • Restricted Boltzmann Machine
  • Deep Belief Network
  1. Part - 8
  • Generative Adversarial Networks
  • Variational Autoencoder
  1. Part - 9
  • Project - 2

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