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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

awesome-quant

**的Quant相关资源索引

barrywang

book_deeplearning_in_pytorch_source

brook

Brook 一键安装脚本

building-machine-learning-pipelines

Code repository for the O'Reilly publication "Building Machine Learning Pipelines" by Hannes Hapke & Catherine Nelson

childish1jin.github.io

coding-interview-university

A complete computer science study plan to become a software engineer.

concourse-pipeline-samples

course-v3

The 3rd edition of course.fast.ai

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论（STAT 157）”教材。

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

dataflowr

code for deep learning courses

datascience_book

datasciencepython

common data analysis and machine learning tasks using python

deep-learning-by-example

Deep Learning By Example, published by Packt

deep-learning-with-keras

Code repository for Deep Learning with Keras published by Packt

deep-learning-with-tensorflow

Deep Learning with TensorFlow by Packt

deeplearning-models

A collection of various deep learning architectures, models, and tips

deeplearningfornlpinpytorch

An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.

dl_study

personal study of 2020 Version of Applications of Deep Neural Networks for TensorFlow and Keras (Washington University in St. Louis) Jeff Heaton

dltest

learning code from d2l.ai

eat_tensorflow2_in_30_days

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

excel-python-da

对比Excel，轻松学习Python数据分析

feature-engineering-made-easy

Feature Engineering Made Easy, published by Packt

getting-things-done-with-pytorch

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

git_test

gluon

googlecolab-test