/Applied-Machine-Learning

https://github.com/Aniruddha-Tapas/Applied-Machine-Learning.git

Primary LanguageJupyter NotebookMIT LicenseMIT

Applied Machine Learning

This repository contains machine learning notebooks from my website appliedprogramming.net. The examples and projects in the repo contain the explantory theory about the different algorithms used and the necessary preprocessing steps to clean, visualize and analyse the data. The datasets for most of the examples are taken from the UCI Machine Learning repository.

Deep Learning using TensorFlow
Introduction to TensorFlow
Transfer Learning for Classifying Animal images
Speech Recognition of Digits
One Shot Learning to Classify Omniglot data
How to use SyntaxNet
Machine Learning using Scikit-Learn
Introduction
Getting Started
Classification
Logistic Regression For Banknote Authentication
Support Vector Machines for Energy-Efficiency Classification
Detecting Faces wearing glasses with Support Vector Machines
Car Evaluation using Decision trees and Random Forests
Zoo Animal Classification using Naive Bayes
Classifying Ionosphere structure using K nearest neigbours
Advanced Scikit-Learn Classification Techniques
Regression
Predicting Electrical Energy Output with Regression Analysis
Air Quality Prediction
Advanced Scikit-Learn Regression Techniques
Clustering
Customer Segmentation For Market Analysis
Seeds Clustering
Applying K-Means for Image Quantization
Ensemble Learning
Ensemble Learning to Classify Patients with Heart Disease
OnlineNewsPopularity Classification using Ensembles
Classifying Default of Credit Card Clients
Examples
Adult Income Classification
Gesture Phase Detection
Student Grade Evaluation
Lenses Data Classification and Clustering
Liver Patient Classification
TicTacToe Move Classification
Connect4 Result Classification
Leaf Classification
Plants Clustering and Classification
Machine Learning using GraphLab Create library
Predicting House Prices using GraphLab Create
Predicting sentiment from product reviews
Building a song recommender
Document Retrieval from Wikipedia data

NOTE: Please feel free to send pull requests and help me improve the code base so that people who want to get into this fascinating field of ML and AI can get the best resources possible! :)