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120-data-science-interview-questions

Answers to 120 commonly asked data science interview questions.

aalto-cs-e4850-computer-vision

Course notes and exercises for Aalto CS-E4850 Computer Vision

awesome-cv

:page_facing_up: Awesome CV is LaTeX template for your outstanding job application

awesome-deep-learning-papers

The most cited deep learning papers

awesome-deep-learning-resources

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully.

bernoullimixtureclassifier

A Bernoulli Mixture classifier for a MNIST dataset classification task.

bios6301

Biostatistics 301: Introduction to Statistical Computing

bios8366

Advanced Statistical Computing at Vanderbilt University's Department of Biostatistics

build-an-ai-startup-with-pytorch

test

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

communitytracking

Tracking communities in Dynamic Social Graphs with algorithms such as Timerank, GED and more. This is a fork from Ilias Sarantopoulos' original implementations.

computerelectronics

A Java e-shop application for a dummy computer electronics shop.

csml_notes

UCL MSc Computational Statistics and Machine Learning Revision Notes

deep-gaussian-process

🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

dlproject

Project for the Deep Learning course on Graph Classification

doors

Backgammon Doors implementation for AI Course using expectiMiniMax with probabilistic a-b pruning and java swing 2.5D graphics. (graphics code to be ultimately refined in the future)

doubly-stochastic-dgp

Deep Gaussian Processes with Doubly Stochastic Variational Inference

fastxml

FastXML / PFastXML / PFastreXML - Implementation of Extreme Multi-label Classification

fbnn

Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

feedforwardneuralnet

A custom made feed-forward neural network with 1 hidden layer developed in Python using NumPy for a MNIST dataset classification task.

gpflow-slim

customized GPflow with simple Tensorflow API

gppvae

Gaussian Process Prior Variational Autoencoder

gpytorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

grpolitics_twitter_sentanalysis

Sentiment Analysis of Greek Political Twitter

hi-vae

high_performance_python

Code for the book "High Performance Python" by Micha Gorelick and Ian Ozsvald with OReilly