Python隨身聽-20200930技術精選

致讀者：親愛的「Python隨身聽」的觀眾們，這是由DE8UG的人工非智能給你帶來的新的一期技術精選。主要為編程初學者，開發工程師，算法工程師，數據分析師，運維，測試，運營，產品等各個崗位的Python愛好者帶來Python世界的流行趨勢，前沿技術。你可以挑選自己喜歡的項目盡情玩耍，任何想法歡迎留言討論。本文的結構和內容會經常更新，每晚10：28分發布（爭取🤡），感謝訂閱🆙和收藏☆。

🤩Python隨身聽-技術精選：/donnemartin/system-design-primer

👉Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
😎TOPICS: programming,development,design,design-system,system,design-patterns,web,web-application,webapp,python,interview,interview-questions,interview-practice
⭐️STARS：108035, 今日上升數↑:152

👉README：

*English ∙ 日本語 ∙ 簡體中文 ∙ 繁體中文 | العَرَبِيَّة‎ ∙ বাংলা ∙ Português do Brasil ∙ Deutsch ∙ ελληνικά ∙ עברית ∙ Italiano ∙ 한국어 ∙ فارسی ∙ Polski ∙ русский язык ∙ Español ∙ [...

地址：https://github.com/donnemartin/system-design-primer

🤩Python隨身聽-技術精選：/home-assistant/core

👉🏡 Open source home automation that puts local control and privacy first
😎TOPICS: python,home-automation,iot,internet-of-things,mqtt,raspberry-pi,asyncio
⭐️STARS：35859, 今日上升數↑:187

👉README：

Home Assistant |Chat Status|

Open source home automation that puts local control and privacy first. Powered by a worldwide community of tinkerers and DIY enthusiasts. Perfect to run on a Raspberry Pi or a local server.

Check out home-assistant.io <https://home-assistant.io>__ for a demo <https://home-assistant.io/demo/>, installation instructions <https://home-assistant.io/getting-started/>,
tutorials <https://home-assistant.io/getting-started/automation-2/>__ and documentation <https://home-assistant.io/docs/>__.

|screenshot-states|

Featured integrations

|screenshot-components|

The system is built using a modular approach so support for other devices or actions can be implemented easily. See also the `section on architecture <htt...

地址：https://github.com/home-assistant/core

🤩Python隨身聽-技術精選：/openai/jukebox

👉Code for the paper "Jukebox: A Generative Model for Music"
😎TOPICS: paper,audio,music,pytorch,generative-model,vq-vae,transformer
⭐️STARS：3339, 今日上升數↑:15

👉README：

Status: Archive (code is provided as-is, no updates expected)

Jukebox

Code for "Jukebox: A Generative Model for Music"

Paper
Blog
Explorer
Colab

Install

Install the conda package manager from https://docs.conda.io/en/latest/miniconda.html

# Required: Sampling
conda create --name jukebox python=3.7.5
conda activate jukebox
conda install mpi4py=3.0.3 # if this fails, try: pip install mpi4py==3.0.3
conda install pytorch=1.4 torchvision=0.5 cudatoolkit=10.0 -c pytorch
git clone https://github.com/openai/jukebox.git
cd jukebox
pip install -r requirements.txt
pip install -e .

# Required: Training
conda install av=7.0.01 -c conda-forge
pip install ./tensorboardX

# Optional: Apex for faster training with fused_adam
conda install pytorch=1.1 torchvision=0.3 cudatoolkit=10.0 -c p...

地址：https://github.com/openai/jukebox

---


## 🤩Python隨身聽-技術精選：/kov4l3nko/MEDUZA
> 👉A more or less universal SSL unpinning tool for iOS
> 😎TOPICS: `ios,ssl-pinning,bypass,certificate-pinning,frida`
> ⭐️STARS：122, 今日上升數↑:20

👉README：

# MEDUZA

"MEDUZA" ("медуза") means "jellyfish" in Ukrainian :ukraine:.



## What is MEDUZA?

It's a [Frida](https://frida.re/)-based tool, my replacement for [SSLKillSwitch](https://github.com/nabla-c0d3/ssl-kill-switch2). I created it for in-house use, but then decided to opensource it. TBH, I hate open source, but the world is full of compromises... :(

## How does it work?

It's simple. First time, you run an app without sniffing and use it as usual. MEDUZA is sitting quietly and collecting certificates used by the app to connect servers. Then MEDUZA generates a Frida script that fakes (==upnin) the collected certificates. So you run the app for second time, use the generated script, and catch the traffic with mitmproxy.

## Limitations

MEDUZA can only unpin apps using iOS system SSL libs. Some apps (e.g. Instagram) do not use the system SSL libs, they implement some third-party custom SSL stack (for example, Instagram uses OpenSSL statically linked to an Instagram private frameworks, see [InstagramSSLP...

地址：https://github.com/kov4l3nko/MEDUZA

---


## 🤩Python隨身聽-技術精選：/Azure/azure-cli
> 👉Azure Command-Line Interface
> 😎TOPICS: `azure,azure-cli,cloud`
> ⭐️STARS：2059, 今日上升數↑:10

👉README：

# Microsoft Azure CLI


A great cloud needs great tools; we're excited to introduce *Azure CLI*, our next generation multi-platform command line experience for Azure.

Take a test run now from Azure Cloud Shell!


## Installation

Please refer to the [install guide](https://docs.microsoft.com/cli/azure/install-azure-cli) for detailed install instructions.

A list of common install issues and their resolutions are available at [install troubleshooting](https://github.com/Azure/azure-cli/blob/dev/doc/install_troubleshooting.md).

### Developer installation (see below)

- [Docker](#docker)
- [Edge Builds](#edge-builds)
- [Developer Setup](#developer-setup)

## Usage

```bash
$ az [ group ] [ subgroup ] [ command ] {parameters}

Get Started

Please refer to the "get started" guide for in-depth instructions.

For usage and help content, pass in the -h parameter, for example:

$ az storage -h
$ az vm create -h

Highlights

He...

地址：https://github.com/Azure/azure-cli

🤩Python隨身聽-技術精選：/mingrammer/diagrams

👉🎨 Diagram as Code for prototyping cloud system architectures
😎TOPICS: diagram,diagram-as-code,drawing,architecture,prototyping
⭐️STARS：9170, 今日上升數↑:352

👉README：

Diagrams

Diagram as Code.

Diagrams lets you draw the cloud system architecture in Python code. It was born for prototyping a new system architecture design without any design tools. You can also describe or visualize the existing system architecture as well. Diagrams currently supports main major providers including: AWS, Azure, GCP, Kubernetes, Alibaba Cloud, Oracle Cloud etc... It also supports On-Premise nodes, SaaS and major Programming frameworks and languages.

Diagram as Code also allows you to track the architecture diagram changes in any version control system.

NOTE: It does not control any actual cloud resources nor does it generate cloud formation or terra...

地址：https://github.com/mingrammer/diagrams

🤩Python隨身聽-技術精選：/django/django

👉The Web framework for perfectionists with deadlines.
😎TOPICS: python,django,web,framework,orm,templates,models,views,apps
⭐️STARS：52467, 今日上升數↑:58

👉README：

======
Django

Django is a high-level Python Web framework that encourages rapid development
and clean, pragmatic design. Thanks for checking it out.

All documentation is in the "docs" directory and online at
https://docs.djangoproject.com/en/stable/. If you're just getting started,
here's how we recommend you read the docs:

First, read docs/intro/install.txt for instructions on installing Django.

Next, work through the tutorials in order (docs/intro/tutorial01.txt,
docs/intro/tutorial02.txt, etc.).

If you want to set up an actual deployment server, read
docs/howto/deployment/index.txt for instructions.

You'll probably want to read through the topical guides (in docs/topics)
next; from there you can jump to the HOWTOs (in docs/howto) for specific
problems, and check out the reference (docs/ref) for gory details.

See docs/README for instructions on building an HTML version of the docs.

Docs are updated rigorously. If you find any problems in t...

地址：https://github.com/django/django

🤩Python隨身聽-技術精選：/public-apis/public-apis

👉A collective list of free APIs for use in software and web development.
😎TOPICS: ``
⭐️STARS：97138, 今日上升數↑:68

👉README：

A collective list of free APIs for use in software and web development.

A public API for this project can be found here!

For information on contributing to this project, please see the contributing guide.

Please note a passing build status indicates all listed APIs are available since the last update. A failing build status indicates that 1 or more services may be unavailable at the moment.

Index

地址：https://github.com/public-apis/public-apis

🤩Python隨身聽-技術精選：/parzulpan/real-live

👉A cross-platform network media aggregation application that supports online viewing or listening of live video, HD TV and radio stations. 一個跨平臺的網絡媒體聚合應用，支持直播視頻，高畫質電視和廣播電臺的在線觀看或收聽。
😎TOPICS: cross-platform,media,livestream,live,live-video,hdtv,radio-station
⭐️STARS：520, 今日上升數↑:49

👉README：

RealLive

簡體中文 | 繁體中文 | English

一個跨平臺的網絡媒體聚合應用，支持直播視頻，高畫質電視和廣播電臺的在線觀看或收聽。

桌面端：

使用視頻

為什麼是它

它解決了什麼？

懷念電視和電臺嗎？它就能滿足你；

多種資源設置攜帶？它讓你隨時隨地看；

多個平臺往返切換？它即能支持多個平臺和頻道。

它有什麼特性？

多端支持，包括 Linux、MacOS、Windows 等桌面端，Android、iOS 等移動端，Web 端，後端等；

多平臺和頻道支持，只要能得到流媒體的數據均可以觀看或收聽，不斷拓展更新中；

支持查看熱門直播、數據備份和恢復、筆記功能和各種偏好設置；

它未來會如何？

打通各端數據，支持數據緩存和搜尋引擎；

持續更新各種平臺或平臺；

支持機器翻譯和智能字幕；

更多功能和特性等待發掘。

快速開始

分支說明：

桌面端調試運行：

配置好 Python 開發環境，推薦 Python3.6+。

首次使用時，Fork 後 Clone 該項目，進入 src/real-live-desktop 桌面端項目文件夾，配置 DebugRun.sh後，然後運行 DebugRun.sh。

git clone -b dev https://github.com/parzulpan/real-live.git
./DebugRun.sh

非首次使用時，即配置好環境後，...

地址：https://github.com/parzulpan/real-live

🤩Python隨身聽-技術精選：/anandpawara/Real_Time_Image_Animation

👉The Project is real time application in opencv using first order model
😎TOPICS: ``
⭐️STARS：2051, 今日上升數↑:107

👉README：

Real time Image Animation

The Project is real time application in opencv using first order model

Steps to setupStep 1: Create virtual environment

Python version : python v3.7.3 or higher

create virual environment : pip install virtualenv

activate virtual environment : virtualenv env

Step 2: Activate virtual environment

For windows : env/Script/activate

For Linux : source env/bin/activate

Step 3 : Install required modules

Install modules : pip install -r requirements.txt

Install pytorch and torchvision : pip install torch===1.0.0 torchvision===0.2.1 -f https://download.pytorch.org/whl/cu100/torch_stable.html

Step 4 : Download cascade file ,weights and model and save in folder named extract

gdown --id 1wCzJP1XJNB04vEORZvPjNz6drkXm5AUK
The file is also availible via direct link on Google's Drive:
https://drive.google.com/uc?id=1wCzJP1XJNB04vEORZvPjNz6drkXm5AUK

On Linux machine : unzip checkpoints.zip...

地址：https://github.com/anandpawara/Real_Time_Image_Animation

🤩Python隨身聽-技術精選：/apprenticeharper/DeDRM_tools

👉DeDRM tools for ebooks
😎TOPICS: ``
⭐️STARS：8387, 今日上升數↑:62

👉README：

DeDRM_tools

DeDRM tools for ebooks

This is a repository of all the scripts and other tools for removing DRM from ebooks that I could find, committed in date order as best as I could manage. (Except for the Requiem tools for Apple's iBooks, and Convert LIT for Microsoft's .lit ebooks.)

Mostly it tracks the tools released by Apprentice Alf, athough it also includes the individual tools and their histories from before Alf had a blog.

Users should download the latest zip archive.
Developers might be interested in forking the repository, as it contains unzipped versions of those tools that are zipped to make the changes over time easier to follow.

For the latest Amazon KFX format, users of the calibre plugin should also install the KFX Input pl...

地址：https://github.com/apprenticeharper/DeDRM_tools

🤩Python隨身聽-技術精選：/domokane/FinancePy

👉A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
😎TOPICS: risk,pricing,risk-management,asset-allocation,finance,valuation,python,derivatives-pricing,numba,bonds,students,fixed-income,derivatives,investment,currency,credit
⭐️STARS：86, 今日上升數↑:30

👉README：

FinancePy

FinancePy is a python-based library that is currently in beta version. It covers the following functionality:

Although it is written entirely in Python, it can achieve speeds comparable to C++ by using Numba. As a result the user has both the ability to examine the underlying code and the ability to perform pricing and risk at speeds which compare to a library written in C++.

The target audience for this library includes:

Students wishing to learn derivative pricing and Python.

Professors wishing to teach derivative pricing and Python.

Traders wishing to price or risk-manage a derivative.

Quantitative analysts seeking to price or reverse engineer a price.

Risk managers wishing to replicate and understand a price.

Portfolio managers wishing to check prices or calculate risk measures

Fund managers wanting to value a portfolio or examine a trading strategy

Structurers or financial en...

地址：https://github.com/domokane/FinancePy

🤩Python隨身聽-技術精選：/Ciphey/Ciphey

👉⚡ Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes ⚡
😎TOPICS: decryption,natural-language-processing,cryptography,cipher,artificial-intelligence,ctf-tools,ctf,cpp,python,hacking,pentesting,deep-neural-network,hashes,cyberchef-magic,encryptions,encodings
⭐️STARS：4588, 今日上升數↑:35

👉README：

】

    https://github.com/Ciphey/Ciphey

🤩Python隨身聽-技術精選：/facebookresearch/SlowFast

👉PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
😎TOPICS: ``
⭐️STARS：2960, 今日上升數↑:7

👉README：

PySlowFast

PySlowFast is an open source video understanding codebase from FAIR that provides state-of-the-art video classification models with efficient training. This repository includes implementations of the following methods:

SlowFast Networks for Video Recognition

Non-local Neural Networks

A Multigrid Method for Efficiently Training Video Models

X3D: Progressive Network Expansion for Efficient Video RecognitionIntroduction

The goal of PySlowFast is to provide a high-performance, light-weight pytorch codebase provides state-of-the-art video backbones for video understanding research on different tasks (classification, detection, and etc). It is designed in order to support rapid implementation and evaluation of novel video research ideas. PySlowFast includes implementatio...

地址：https://github.com/facebookresearch/SlowFast

🤩Python隨身聽-技術精選：/ultralytics/yolov5

👉YOLOv5 in PyTorch > ONNX > CoreML > iOS
😎TOPICS: yolov3,yolov4,yolov5,object-detection,pytorch,onnx,coreml,ios,tflite
⭐️STARS：5163, 今日上升數↑:23

👉README：

  

This repository represents Ultralytics open-source research into future object detection methods, and incorporates our lessons learned and best practices evolved over training thousands of models on custom client datasets with our previous YOLO repository https://github.com/ultralytics/yolov3. All code and models are under active development, and are subject to modification or deletion without notice. Use at your own risk.

** GPU Speed measures end-to-end time per image averaged over 5000 COCO val2017 images using a V100 GPU with batch size 32, and includes image preprocessing, PyTorch FP16 inference, postprocessing and NMS. EfficientDet data from [google/automl](https://github.co...

地址：https://github.com/ultralytics/yolov5

🤩Python隨身聽-技術精選：/Dod-o/Statistical-Learning-Method_Code

👉手寫實現李航《統計學習方法》書中全部算法
😎TOPICS: machine-learning-algorithms,code,statistical-learning-method
⭐️STARS：6184, 今日上升數↑:10

👉README：

前言

力求每行代碼都有注釋，重要部分註明公式來源。具體會追求下方這樣的代碼，學習者可以照著公式看程序，讓代碼有據可查。

如果時間充沛的話，可能會試著給每一章寫一篇博客。先放個博客連結吧：傳送門。

註：其中Mnist數據集已轉換為csv格式，由於體積為107M超過限制，改為壓縮包形式。下載後務必先將Mnist文件內壓縮包直接解壓。另：有意向為這個repo補充第二版無監督部分的大佬下拉到最下方聯繫我～只要求注釋完善即可。我們可以成為好朋友一起衝鴨！！！實現第二章 感知機：

博客：統計學習方法|感知機原理剖析及實現
實現：perceptron/perceptron_dichotomy.py

第三章 K近鄰：

博客：統計學習方法|K近鄰原理剖析及實現
實現：KNN/KNN.py

第四章 樸素貝葉斯：

博客：統計學習方法|樸素貝葉斯原理剖析及實現
實現：NaiveBayes/NaiveBayes.py

第五章 決策樹：

博客：[統計學習方法|決策樹原理剖析及實現](http://www.pkudodo.com/2018/...

地址：https://github.com/Dod-o/Statistical-Learning-Method_Code

🤩Python隨身聽-技術精選：/plotly/dash

👉Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.
😎TOPICS: dash,plotly,data-visualization,data-science,gui-framework,flask,react,python,finance,bioinformatics,technical-computing,charting,plotly-dash,web-app,productivity,modeling,r,rstats,jupyter,julia
⭐️STARS：12966, 今日上升數↑:14

👉README：

DashDash is a Python framework for building analytical web applications. No JavaScript required.

Built on top of Plotly.js, React and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs directly to your analytical Python code. Read our tutorial proudly crafted ❤️ by Dash itself.

App Samples

To learn more about Dash, read the [extensive announcement letter](https://medium.com/@plotlygraphs/introducing-dash-5ecf...

地址：https://github.com/plotly/dash

🤩Python隨身聽-技術精選：/getsentry/sentry

👉Sentry is cross-platform application monitoring, with a focus on error reporting.
😎TOPICS: crash-reporting,crash-reports,error-monitoring,monitoring,devops,csp-report,django,error-logging
⭐️STARS：26183, 今日上升數↑:11

👉README：

Users and logs provide clues. Sentry provides answers.

What's Sentry?

Sentry is a service that helps you monitor and fix crashes
in realtime. The server is in Python, but it contains a full API for
sending events from any language, in any application.

 

Official Sentry SDKs

地址：https://github.com/getsentry/sentry

🤩Python隨身聽-技術精選：/mirumee/saleor

👉A modular, high performance, headless e-commerce storefront built with Python, GraphQL, Django, and ReactJS.
😎TOPICS: python,e-commerce,django,storefront,store,commerce,shop,ecommerce-storefront,ecommerce,cart,ecommerce-platform,react,pwa,graphql,headless,headless-ecommerce,headless-commerce
⭐️STARS：9160, 今日上升數↑:16

👉README：

Saleor Commerce

Customer-centric e-commerce on a modern stack

A headless, GraphQL-first e-commerce platform delivering ultra-fast, dynamic, personalized shopping experiences. Beautiful online stores, anywhere, on any device.

Join our active, engaged community:
Website | Blog | Twitter | Gitter | Spectrum

 https://github.com/mirumee/saleor

🤩Python隨身聽-技術精選：/scrapy/scrapy

👉Scrapy, a fast high-level web crawling & scraping framework for Python.
😎TOPICS: python,scraping,crawling,framework,crawler
⭐️STARS：38389, 今日上升數↑:17

👉README：

======
Scrapy

.. image:: https://img.shields.io/pypi/v/Scrapy.svg
:target: https://pypi.python.org/pypi/Scrapy
:alt: PyPI Version

.. image:: https://img.shields.io/pypi/pyversions/Scrapy.svg
:target: https://pypi.python.org/pypi/Scrapy
:alt: Supported Python Versions

.. image:: https://img.shields.io/travis/scrapy/scrapy/master.svg
:target: https://travis-ci.org/scrapy/scrapy
:alt: Build Status

.. image:: https://img.shields.io/badge/wheel-yes-brightgreen.svg
:target: https://pypi.python.org/pypi/Scrapy
:alt: Wheel Status

.. image:: https://img.shields.io/codecov/c/github/scrapy/scrapy/master.svg
:target: https://codecov.io/github/scrapy/scrapy?branch=master
:alt: Coverage report

.. image:: https://anaconda.org/conda-forge/scrapy/badges/version.svg
:target: https://anaconda.org/conda-forge/scrapy
:alt: Conda Version

Overview

Scrapy is a fast high-level web crawling and web scraping framework, used to
crawl websites and extract structured data from t...

地址：https://github.com/scrapy/scrapy

🤩Python隨身聽-技術精選：/HuiZeng/Image-Adaptive-3DLUT

👉Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time
😎TOPICS: 3d-luts,photo-retouching,image-enhancement,color-enhancement,color-manipulation,computational-photography,image-processing
⭐️STARS：127, 今日上升數↑:26

👉README：

Image-Adaptive-3DLUT

Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time

DownloadsPaper, Supplementary, Dataset, [PCT patent]

The whole datasets used in the paper are over 300G. Here I only provided the FiveK dataset resized into 480p resolution (including 8-bit sRGB, 16-bit XYZ inputs and 8-bit sRGB targets). I also provided 10 full-resolution images for testing speed. To obtain the entire full-resolution images, it is recommended to transform from the original FiveK dataset.

A model trained on the 480p resolution can be directly applied to images of 4K (or higher) resolution without performance drop. This can significantly speedup the trainin...

地址：https://github.com/HuiZeng/Image-Adaptive-3DLUT

🤩Python隨身聽-技術精選：/matterport/Mask_RCNN

👉Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
😎TOPICS: ``
⭐️STARS：18439, 今日上升數↑:33

👉README：

Mask R-CNN for Object Detection and Segmentation

This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet101 backbone.

The repository includes:

Source code of Mask R-CNN built on FPN and ResNet101.

Training code for MS COCO

Pre-trained weights for MS COCO

Jupyter notebooks to visualize the detection pipeline at every step

ParallelModel class for multi-GPU training

Evaluation on MS COCO metrics (AP)

Example of training on your own dataset

The code is documented and designed to be easy to extend. If you use it in your research, please consider citing this repository (bibtex below). If you work on 3D vision, you might find our recently released Matterport3D dataset useful as well.
This dataset was ...

地址：https://github.com/matterport/Mask_RCNN

🤩Python隨身聽-技術精選：/lmoroney/dlaicourse

👉Notebooks for learning deep learning
😎TOPICS: ``
⭐️STARS：4068, 今日上升數↑:7

👉README：

...

地址：https://github.com/lmoroney/dlaicourse

🤩Python隨身聽-技術精選：/Kulbear/deep-learning-coursera

👉Deep Learning Specialization by Andrew Ng on Coursera.
😎TOPICS: deep-learning,coursera
⭐️STARS：5815, 今日上升數↑:6

👉README：

Deep Learning Specialization on Coursera

Master Deep Learning, and Break into AI

Instructor: Andrew Ng

Introduction

This repo contains all my work for this specialization. All the code base, quiz questions, screenshot, and images, are taken from, unless specified, Deep Learning Specialization on Coursera.

What I want to say

VERBOSE CONTENT WARNING: YOU CAN JUMP TO THE NEXT SECTION IF YOU WANT

As a CS major student and a long-time self-taught learner, I have completed many CS related MOOCs on Coursera, Udacity, Udemy, and Edx. I do understand the hard time you spend on understanding new concepts and debugging your program. There are discussion forums on most MOOC platforms, however, even a question with detailed description may need some time to be answered. Here I released these solutions, which are only for your reference purpose. It may help you to save some time. And I hope you don't copy any pa...

地址：https://github.com/Kulbear/deep-learning-coursera

🤩Python隨身聽-技術精選：/ageron/handson-ml2

👉A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
😎TOPICS: ``
⭐️STARS：10415, 今日上升數↑:16

👉README：

Machine Learning Notebooks

This project aims at teaching you the fundamentals of Machine Learning in
python. It contains the example code and solutions to the exercises in the second edition of my O'Reilly book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow:Note: If you are looking for the first edition notebooks, check out ageron/handson-ml.

Quick StartWant to play with these notebooks online without having to install anything?

Use any of the following services.

WARNING: Please be aware that these services provide temporary environments: anything you do will be deleted after a while, so make sure you download any data you care about.

地址：https://github.com/ageron/handson-ml2

🤩Python隨身聽-技術精選：/awslabs/amazon-sagemaker-examples

👉Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
😎TOPICS: amazon,sagemaker,example,notebooks,machine,deep,learning,aws,rl,reinforcement-learning
⭐️STARS：4271, 今日上升數↑:6

👉README：

Amazon SageMaker Examples

This repository contains example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker

ExamplesIntroduction to Ground Truth Labeling Jobs

These examples provide quick walkthroughs to get you up and running with the labeling job workflow for Amazon SageMaker Ground Truth.

Bring your own model for sagemaker labeling workflows with active learning is an end-to-end example that shows how to bring your custom training, inference logic and active learning to the Amazon SageMaker ecosystem.

From Unlabeled Data to a Deployed Machine Learning Model: A SageMaker Ground Truth Demonstration for Image Classification is an end-to-end example that starts with an unlabeled dataset, label...

地址：https://github.com/awslabs/amazon-sagemaker-examples

🤩Python隨身聽-技術精選：/Pierian-Data/Complete-Python-3-Bootcamp

👉Course Files for Complete Python 3 Bootcamp Course on Udemy
😎TOPICS: ``
⭐️STARS：12258, 今日上升數↑:18

👉README：

Complete-Python-3-Bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

Get it now for ...

地址：https://github.com/Pierian-Data/Complete-Python-3-Bootcamp

🤩Python隨身聽-技術精選：/Atcold/pytorch-Deep-Learning

👉Deep Learning (with PyTorch)
😎TOPICS: jupyter-notebook,pytorch,deep-learning,neural-nets
⭐️STARS：2848, 今日上升數↑:9

👉README：

This notebook repository now has a companion website, where all the course material can be found in video and textual format.

🇬🇧   🇨🇳   🇰🇷   🇪🇸   🇮🇹   🇹🇷   🇯🇵   [🇸🇦](https://github.com/Atcold/pytorch-Deep-Learning/blob/master/docs/ar/README-AR.m...

地址：https://github.com/Atcold/pytorch-Deep-Learning

🤩Python隨身聽-技術精選：/KaihuaTang/Long-Tailed-Recognition.pytorch

👉[NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation (LVIS). It is also a PyTorch implementation of the NeurIPS 2020 paper 'Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect'.
😎TOPICS: ``
⭐️STARS：125, 今日上升數↑:17

👉README：

A Strong Single-Stage Baseline for Long-Tailed Problems

This project provides a strong single-stage baseline for Long-Tailed Classification (under ImageNet-LT, Long-Tailed CIFAR-10/-100 datasets), Detection, and Instance Segmentation (under LVIS dataset). It is also a PyTorch implementation of the NeurIPS 2020 paper Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect, which proposes a general solution to remove the bad momentum causal effect for a variety of Long-Tailed Recognition tasks. The codes are organized into three folders:

The classification folder supports long-tailed classification on ImageNet-LT, Long-Tailed CIFAR-10/CIFAR-100 datasets.

The lvis_old folder (deprecated) supports long-tailed object detection and instance segmentation on LVIS V0.5 dataset, which is built on top of mmdet V1.1.

The latest version of long-tailed detection and instance segmentation is under [lvis1.0 ...

地址：https://github.com/KaihuaTang/Long-Tailed-Recognition.pytorch

🤩Python隨身聽-技術精選：/timsainb/ParametricUMAP_paper

👉Parametric UMAP embeddings for representation and semisupervised learning. From the paper "Parametric UMAP: learning embeddings with deep neural networks for representation and semi-supervised learning" (Sainburg, McInnes, Gentner, 2020).
😎TOPICS: umap,dimensionality-reduction,semisupervised-learning,representation-learning,machine-learning
⭐️STARS：65, 今日上升數↑:19

👉README：

Parametric UMAP (2020; Code for paper)

This repository contains the code needed to reproduce the results in the paper "Parametric UMAP: learning embeddings with deep neural networks for representation and semi-supervised learning" by Sainburg, McInnes, and Gentner (2020).

Citation:

@article{parametricumap,
title={Parametric UMAP: learning embeddings with deep neural networks for representation and semi-supervised learning},
author={Sainburg, Tim and McInnes, Leland and Gentner, Timothy Q},
}

How to use

The main implementation of this code is available in umap.parametric_umap in the UMAP repository (v0.5+). Most people reading this will want to use that code, and can ignore this repository.

The code in this repository is the 'messy' version. It has custom training loops which are a bit more verbose and customizable. It might be more useful for integrating UMAP into your custom models.

The code can be installed w...

地址：https://github.com/timsainb/ParametricUMAP_paper

🤩Python隨身聽-技術精選：/geekquad/AlgoBook

👉A beginner-friendly project to help you in open-source contributions. Made specifically for contributions in HACKTOBERFEST 2020! Algorithms in Python and Machine Learning. Please leave a star ⭐ to support this project! ✨
😎TOPICS: hactoberfest,hactoberfest2020,first-timers,first-pull-request,first-pull-request-and-commit,first-contributions,good-first-issue,open-source,beginner,beginner-friendly,digitalocean,easy-to-use,github,up-for-grabs,machine-learning,python,python3,machinelearning,pr-welcome
⭐️STARS：33, 今日上升數↑:13

👉README：

A beginner friendly project to help you in open source contributions. An attempt to bring all the algorithms together.

Please see the Contributing Guidelines .

Join the community on Slack.

Overview

The goal of this project is to help the beginners with their contributions in Open Source and bring all the possible algorithms of Machine Learning and Python together. We aim to achieve this collaboratively, so feel free to contribute in any way you want, just make sure to follow the contribution guidelines.

For now, this repo is focused on the beginner frienldy contributions in Hacktoberfest 2020.

The open source community provides a great opportunity for aspiring ...

地址：https://github.com/geekquad/AlgoBook

🤩Python隨身聽-技術精選：/kubernetes/community

👉Kubernetes community content
😎TOPICS: kubernetes
⭐️STARS：7034, 今日上升數↑:9

👉README：

Kubernetes Community

Welcome to the Kubernetes community!

This is the starting point for joining and contributing to the Kubernetes community - improving docs, improving code, giving talks etc.

To learn more about the project structure and organization, please refer to [Project Governance] information.

Communicating

The communication page lists communication channels like chat,
issues, mailing lists, conferences, etc.

For more specific topics, try a SIG.

Governance

Kubernetes has the following types of groups that are officially supported:

Committees are named sets of people that are chartered to take on sensitive topics.
This group is encouraged to be as open as possible while achieving its mission but, because of the nature of the topics discussed, private communications are allowed.
Examples of committees include the steering committee and things like security or code of conduct.

Special Interest Groups (SIGs) are persistent open groups that focus on a par...

地址：https://github.com/kubernetes/community

🤩Python隨身聽-技術精選：/tensorflow/docs

👉TensorFlow documentation
😎TOPICS: tensorflow,tensorflow-tutorials,tensorflow-examples,documentation,machine-learning,deep-learning,deep-neural-networks
⭐️STARS：3847, 今日上升數↑:9

👉README：

TensorFlow Documentation

These are the source files for the guide and tutorials on
tensorflow.org.

To contribute to the TensorFlow documentation, please read
CONTRIBUTING.md, the
TensorFlow docs contributor guide,
and the style guide.

To file a docs issue, use the issue tracker in the
[tensorflow/tensorflow](https://github.com/tensorflow/tensorflow/issues/new?template=20-docum...

地址：https://github.com/tensorflow/docs

🤩Python隨身聽-技術精選：/CoreyMSchafer/code_snippets

👉None
😎TOPICS: ``
⭐️STARS：5771, 今日上升數↑:7

👉README：

code_...

地址：https://github.com/CoreyMSchafer/code_snippets

🤩Python隨身聽-技術精選：/tensorflow/examples

👉TensorFlow examples
😎TOPICS: tensorflow,tensorflow-examples
⭐️STARS：3920, 今日上升數↑:11

👉README：

TensorFlow Examples

Most important links!

If you are looking to learn TensorFlow, don't miss the
core TensorFlow documentation
which is largely runnable code.
Those notebooks can be opened in Colab from
tensorflow.org.

What is this repo?

This is the TensorFlow example repo. It has several classes of material:

地址：https://github.com/tensorflow/examples

🤩Python隨身聽-技術精選：/Mikoto10032/DeepLearning

👉深度學習入門教程, 優秀文章, Deep Learning Tutorial
😎TOPICS: deeplearning,cnn,rnn,gan,machine-learning,tensorflow,mxnet,deep-learning,machinelearning,pytorch,gcn,kaggle
⭐️STARS：3696, 今日上升數↑:14

👉README：

DeepLearning Tutorial一. 入門資料

完備的 AI 學習路線，最詳細的中英文資源整理 ⭐

AiLearning: 機器學習 - MachineLearning - ML、深度學習 - DeepLearning - DL、自然語言處理 NL

Machine-Learning

數學基礎

矩陣微積分

機器學習的數學基礎

CS229線性代數與概率論基礎

機器學習基礎快速入門

地址：https://github.com/Mikoto10032/DeepLearning

🤩Python隨身聽-技術精選：/dafriedman97/mlbook

👉Repository for the free online book Machine Learning from Scratch (link below!)
😎TOPICS: ``
⭐️STARS：310, 今日上升數↑:34

👉README：

Machine Learning from Scratch

Welcome to the repo for my free online book, "Machine Learning from Scratch".
The book itself can be found here.
(A somewhat ugly version of) the PDF can be found in the book.pdf file above in the master branch. No...

地址：https://github.com/dafriedman97/mlbook

🤩Python隨身聽-技術精選：/mozilla/TTS

👉🤖 💬 Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
😎TOPICS: deep-learning,mozilla,text-to-speech,python,pytorch,tacotron,tts,speaker-encoder,dataset-analysis,tacotron2,tensorflow2,vocoder,melgan,gantts,multiband-melgan,mozilla-tts,glow-tts,speech
⭐️STARS：2645, 今日上升數↑:6

👉README：

" width="320" height="95" />

  

This project is a part of Mozilla Common Voice.

Mozilla TTS aims a deep learning based Text2Speech engine, low in cost and high in quality.

You can check some of synthesized voice samples from here.

If you are new, you can also find here a brief post about some of TTS architectures and here list of up-to-date research papers.

TTS Performancehttps://github.com/mozilla/TTS🤩Python隨身聽-技術精選：/rasbt/deeplearning-models

👉A collection of various deep learning architectures, models, and tips
😎TOPICS: ``
⭐️STARS：13475, 今日上升數↑:7

👉README：

Deep Learning Models

A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks.

Traditional Machine Learning

Perceptron
   [TensorFlow 1: GitHub | Nbviewer]
   [PyTorch: GitHub | Nbviewer]

Logistic Regression
   [TensorFlow 1: GitHub | Nbviewer]
   [PyTorch: GitHub | [Nbviewer](https://nbviewer.jupyter.org/github/rasbt/deeplearning-...

地址：https://github.com/rasbt/deeplearning-models

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