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aas

Code to accompany Advanced Analytics with Spark from O'Reilly Media

awesome-automl-papers

A curated list of automated machine learning papers, articles, tutorials, slides and projects

awesome-meta-learning

A curated list of Meta-Learning resources/papers.

bayesian-deep-learning-notes

A list of notes on Bayesian deep learning papers

d2l-zh

《动手学深度学习》，英文版即伯克利深度学习（STAT 157，2019春）教材。面向中文读者、能运行、可讨论。

experiments

gitignore

A collection of useful .gitignore templates

gpy

Gaussian processes framework in python

gpyopt

Gaussian Process Optimization using GPy

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

mastering-vim

Mastering Vim, published by Packt

nndl.github.io

《神经网络与深度学习》 Neural Network and Deep Learning

paramz

Parameterization Framework for parameterized model creation and handling.

patchwork

All the Git-it Workshop completers!

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

python-automation-cookbook

Python Automation Cookbook, published by Packt

rstat131

some scripts associated with STAT131: Time Series & Prediction

stanford-tensorflow-tutorials

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