ome-ga Goto Github PK

100-days-of-ml-code

100 Days of ML Coding

12306

12306智能刷票，订票

955.wlb

955 不加班的公司名单 - 工作 955，work–life balance (工作与生活的平衡)

algo

Data Structure & Algorithm

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

amd-hackintosh

Hackintosh-Opencore-5600X-Asus-TUF-Gaming-B550M-Plus-WI-FI-RX5500XT

an-introduction-to-statistical-learning

This repository contains the exercises and its solution contained in the book An Introduction to Statistical Learning in python.

andrew-ng-deeplearning.ai

Andrew Ng Deeplearning.ai Course Notes

awesome-algorithm

LeetCode, HackRank, 剑指offer, classic algorithm implementation

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

benchmarking-keras-pytorch

Reproducible Benchmarking of Keras and PyTorch Models

bigdata-notes

大数据入门指南 :star:

caculator-tkinter

Make a simple caculator using python-tkinter for practice

chinese-dos-games-web

🌐 Source code of https://dos.zczc.cz

coursera-ml-py

Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

cs231n-2018

My solution for cs231n-2018

cs231n-camp

cs231n training camp

ctr_nn

基于深度学习的CTR预估，从FM推演各深度学习CTR预估模型（附代码）

cvnd---image-captioning-project

data-science--cheat-sheet

Cheat Sheets

dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

deep-learning-21-examples

《21个项目玩转深度学习———基于TensorFlow的实践详解》配套代码

deep-learning-papers-reading-roadmap

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

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deep_learning_object_detection

A paper list of object detection using deep learning.

deepinterests

深度有趣

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，近30万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

djangoblog

🍺基于Django的博客系统

dnc

Simple RNN, LSTM and Differentiable Neural Computer in pure Numpy