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miscellaneous

ml-from-scratch

Bare bones Python implementations of some of the fundamental Machine Learning models and algorithms.

ml_for_hackers

Code accompanying the book "Machine Learning for Hackers"

mnist_neural_net

Simple Neural Network for MNIST Dataset: http://yann.lecun.com/exdb/mnist/

neural-networks

Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.

nvdm

neural variational document model

ocr-neural-net

pandas_exercises

Practice your pandas skills!

playground

Play with neural networks!

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

pylearn2

Warning: This project does not have any current developer. See bellow.

repo-2017

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning

rnn-tutorial

Recurrent Neural Networks - A Short TensorFlow Tutorial

roamresearch

rubikscube

scikit-learn

scikit-learn: machine learning in Python

scipy_2015_sklearn_tutorial

Scikit-Learn tutorial material for Scipy 2015

soft-eng-interview-prep

Everything you need to know for a Software Engineering interview

stanford-tensorflow-tutorials

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

system_design

Preparation links and resources for system design questions

tensorflow-tutorials

TensorFlow Tutorials with YouTube Videos

tensorflow_multigpu_imagenet

Tensorflow code for training different architectures(DenseNet, ResNet, AlexNet, GoogLeNet, VGG, NiN) on ImageNet dataset + Multi-GPU support + Transfer Learning support

tutorial_theano

Common Code Workflow tutorial on Theano

ubuntu-ranking-dataset-creator

A script that creates train, valid and test datasets for the ranking task from Ubuntu corpus dialogs.

xcluster

Algorithms and evaluation tools for extreme clustering