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cs_offer

计算机学科基础知识和主流编程语言相关内容的总结

datasets

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

deep-learning-book

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

docker

effectivetensorflow

TensorFlow tutorials and best practices.

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

gbmandxgboost

GBMandXGBoost调参

hadoop-book

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

lark

LAnguage Representations Kit

learn-pandas

Tutorials on how to use pandas effectively to do data analysis

learnpython

linux

linux command and shell

mcmc-sampling

The theory and implement of Metropolis Hastings Algorithm and Gibbs sampling

ml_code

ML_R_Code

natural-language-processing-python-and-nltk

Natural Language Processing Python and NLTK by Packt

neural-network-with-financial-time-series-data

This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using Keras on top of Tensor Flow

neural-stock-market-prediction

Uses back-propagating artificial neural networks (ANNs) and historic stock market prices to predict the future trend of stock exchange.

nlptutorial

A Tutorial about Programming for Natural Language Processing

nltk-cheatsheet

Notes from Python's NLTK book

prml-python

programing

python-skills

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

readme

README文件语法解读，即Github Flavored Markdown语法介绍

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

spark-ml-source-analysis

spark ml 算法原理剖析以及具体的源码实现分析

spark-programming-guide-zh-cn

Spark 编程指南简体中文版

stockpredictionrnn

High Frequency Trading Price Prediction using LSTM Recursive Neural Networks