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machine-learning's Introduction

Machine Learning:

This repository consist of the following projects:

Machine Learning with R

Real world examples of Machine Learning :

a) Regression b) Classification c) Nearest Neighbor d) Boosting e) Feature Engineering f) Time Series forecasting

Machine Learning with Python

Real world examples of Machine Learning using (Sci-kit Learn, GraphLab[Dato], TensorFlow) :

a) Regression b) Deep Learning c) Classification d) Support Vector Machine e) Boosting f) Churn Analytics

Also some basic web scraping using Beautiful Soup.

Predictive Analytics Service

This project exposes the various machine learning models (Classifier, Recommender System, Topic Modeling, Text Summarization, Forecasting Trends,etc) as web service(rest). Its shows how to deploy & use machine learning in production after the model is build, validated and evaluated.

Mahout Analytics

This projects contains the Recommender system ,Classification and Clustering example with Apache Mahout.

Churn Analytics

The goal of churn analytics project is to understand the primary drivers to churn and predict churn using R and Apache Mahout.

Natural Language Processing

Some commonly used examples of NLP using OpenNLP, StanfordCoreNLP, LingPipe, Mallet and Carrot :

a) Tokenizer b) Name Finder c) Sentence Detection d) Sentiment Analysis e) POS Detection f) Topic Modeling

Mini Watson

This project is a part of lab exercise done during the course "Analyzing Big Data with a Concept IBM Watson" from Big Data University. Its a simple Question Answering system using OpenNLP.

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