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email-spam-classifier-using-naive-bayes

A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of email subject is first used to train the classifier and then a previously unseen email subject is fed to predict whether it is Spam or Ham.

gam

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

globallocalimagecompletion_tf

Globally and Locally Consistent Image Completion

goodboychan.github.io

jupyter blog

goodrich

The source code for 'Data Structures and Algorithms in Python' by Goodrich, Tamassia, Goldwasser

graph-neural-networks

hadoop-2.x-administration-cookbook

Hadoop 2.x Administration Cookbook, published by Packt

hadoop-algorithms

hadoop-book

Source code to accompany the book "Hadoop in Practice", published by Manning.

hadoop-book-1

Example source code accompanying O'Reilly's "Hadoop: The Definitive Guide" by Tom White

hadoop-framework-examples

An implementation of a real-world map-reduce workflow in each major framework.

hadoop-in-action

Updated samples for the Hadoop in Action title from Manning.

hadoop-kmeans

Python implementation of k-means clustering algorithm in MapReduce.

hcb-v2

hiped2

Source code that accompanies the book "Hadoop in Practice, Second Edition".

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries across different industries.

interactive-choropleth-map-using-python

Contains data and code used to create bokeh application of world obesity choropleth map

inverted-index-hadoop

inverted-index-java

Example code for a mapreduce job which generates an inverted index

islr-python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

jalammar.github.io

Build a Jekyll blog in minutes, without touching the command line.

jhupp-lectures

Notebooks for JHU EN 601.320/420/620

language-translation-english-to-french

This project uses a sequence to sequence model of the recurrent neural network to translate any piece of English text to French. I have used recurrent nets because while training on huge data, recurrent nets actually predict the outcome a lot better than any normal machine learning models. In this specific model, the data first passes through an encoder, comes out as an understanding and passes to a decoder. The decoder generates the output.

machine-learning-book

Code Repository for Machine Learning with PyTorch and Scikit-Learn

machine-learning-coursera

Lecture notes and assignments for coursera machine learning class

machine-learning-yearning-korean-translation

Korean translation of machine learning yearning book by Andrew Ng.

mapreduce

Hadoop Map-Reduce Design Patterns

mapreducealgorithms

Data-Intensive Text Processing with MapReduce

mastering-python-design-patterns-second-edition

Mastering-Python-Design-Patterns-Second-Edition, published by Packt

mia

Mahout in Action Example Code