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👉An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different training environments like Local Machine, Remote Servers, OpenPAI, Kubeflow, <a href=...
👉A Python program to scrape secrets from GitHub through usage of a large repository of dorks.
😎TOPICS: ``
⭐️STARS：435, 今日上升数↑:120
👉README：
GitDorker
GitDorker is a tool that utilizes the GitHub Search API and an extensive list of GitHub dorks that I've compiled from various sources to provide an overview of sensitive information stored on github given a search query.
The Primary purpose of GitDorker is to provide the user with a clean and tailored attack surface to begin harvesting sensitive information on GitHub. GitDorker can be used with additional tools such as GitRob or Trufflehog on interesting repos or users discovered from GitDorker to produce best results.
Rate Limits
GitDorker utilizes the GitHub Search API and is limited to 30 requests per minute. In order to prevent rate limites a sleep function is built into GitDorker after every 30 requests to prevent search failures. Therefore, if one were to run use the alldorks.txt file with GitDorker, the process will take roughly 5 minutes to complete.
Requirements
** Python3
** GitHub Personal Access Token
** Install requirements inside of the requirements.txt file of this ...
When I first learned Python nearly 25 years ago, I was immediately
struck by how I could productively apply it to all sorts of messy work
projects. Fast-forward a decade and I found myself teaching others the
same fun. The result of that teaching is this course--A no-nonsense
treatment of Python that has been actively taught to more than 400
in-person groups since 2007. Traders, systems admins, astronomers,
tinkerers, and even a few hundred rocket scientists who used Python to
help land a rover on Mars--they've all taken this course. Now, I'm
pleased to make it available under a Creative Commons license. Enjoy!
The material you see here is the heart of an instructor-led Python
training course used for corporate training and professional
development. It has been in continual development since 2007 and
battle tested in real-world classrooms. U...
Most of the examples are full-fledged VM examples, which use Vagrant, VirtualBox, and Ansible to boot and configure VMs on your local workstation. Not all playbooks follow all of Ansible's best practices, as they illustrate particular Ansible features in an instructive manner.
Playwright is a Python library to automate Chromium, Firefox and WebKit browsers with a single API. Playwright delivers automation that is ever-green, capable, reliable and fast. See how Playwright is better.
Linux
macOS
Windows
Chromium 86.0.4238.0
✅
✅
✅
WebKit 14.0
✅
✅
✅
Firefox 80.0b8
✅
✅
✅
Headless execution is supported for all browsers on all platforms.
Neural Circuit Policies (NCPs) are designed sparse recurrent neural networks based on the LTC neuron and synapse model loosely inspired by the nervous system of the organism C. elegans.
This page is a description of the Keras (TensorFlow 2.0 package) reference implementation of NCPs.
For reproducibility materials of the paper see the corresponding subpage.
Installation
Requirements:
Python 3.6
TensorFlow 2.0
pip install keras-ncp
Colab notebooks
We have created a few Google Colab notebooks for an interactive introduction to the package
spaCy is a library for advanced Natural Language Processing in Python and
Cython. It's built on the very latest research, and was designed from day one to
be used in real products. spaCy comes with pretrained statistical models and word vectors, and
currently supports tokenization for 60+ languages. It features
state-of-the-art speed, convolutional neural network models for tagging,
parsing and named entity recognition and easy deep learning integration.
It's commercial open-source software, released under the MIT license.
Manim is an animation engine for explanatory math videos. It's used to create precise animations programmatically, as seen in the videos at 3Blue1Brown.
This repository contains the version of manim used by 3Blue1Brown. There is also a community maintained version at https://github.com/ManimCommunity/manim/.
To get help or to join the development effort, please join the discord.
Installation
Manim runs on Python 3.6 or higher version. You can install it from PyPI via pip:
pip3 install manimlib
System requirements are cairo, ffmpeg, sox (optional, if you want to play the prompt tone after running), latex (optional, if you want to use LaTeX).
You can now use it via the manim command. For example:
manim my_project.py MyScene
For more options, take a look at the Using manim sections further below.
Single-package fully conformant lightweight Kubernetes that works on 42
flavours of Linux. Perfect for:
Developer workstations
IoT
Edge
CI/CD
Canonical might have assembled the easiest way to provision a single node Kubernetes cluster - Kelsey Hightower
Why MicroK8s?
Small. Developers want the smallest K8s for laptop and workstation
development. MicroK8s provides a standalone K8s compatible with Azure
AKS, Amazon EKS, Google GKE when you run it on Ubuntu.
Simple. Minimize administration and operations with a single-package
install that has no moving parts for simplicity and certainty. All
dependencies and batteries included.
Secure. Updates are available for all security issues and can be
applied immediately or scheduled...
Abstract: *The style-based GAN architecture (StyleGAN) yields state-of-the-art results in data-driven unconditional generative image modeling. We expose and analyze several of its characteristic artifacts, and propose changes in both model architecture and training methods to address them. In particular, we redesign generator normalization, revisit progressive growing, and regularize the generator to encourage good conditioning in the mapping from latent vectors to images. In addition to improving image quality, this path length regularizer yields the additional benefit that the generator becomes significantly easier to invert. This makes it possible to reliably detect if an image is generated by a particular network. W...
👉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.
Note: If you are looking for the first edition notebooks, check out ageron/handson-ml.
Quick Start
Want 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.
Python随身听-2020-10-18-技术精选
🤩Python随身听-技术精选： /microsoft/nni
👉An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
😎TOPICS:
automl,deep-learning,neural-architecture-search,hyperparameter-optimization,distributed,bayesian-optimization,automated-machine-learning,machine-learning,machine-learning-algorithms,data-science,tensorflow,pytorch,neural-network,deep-neural-network,model-compression,feature-engineering,automated-feature-engineering,nas,python,feature-extraction⭐️STARS：7434, 今日上升数↑:186
👉README：
简体中文
NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture Search, Hyperparameter Tuning and Model Compression.
The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different training environments like Local Machine, Remote Servers, OpenPAI, Kubeflow, <a href=...
地址：https://github.com/microsoft/nni
🤩Python随身听-技术精选： /obheda12/GitDorker
👉A Python program to scrape secrets from GitHub through usage of a large repository of dorks.
😎TOPICS: ``
⭐️STARS：435, 今日上升数↑:120
👉README：
GitDorker
GitDorker is a tool that utilizes the GitHub Search API and an extensive list of GitHub dorks that I've compiled from various sources to provide an overview of sensitive information stored on github given a search query.
The Primary purpose of GitDorker is to provide the user with a clean and tailored attack surface to begin harvesting sensitive information on GitHub. GitDorker can be used with additional tools such as GitRob or Trufflehog on interesting repos or users discovered from GitDorker to produce best results.
Rate Limits
GitDorker utilizes the GitHub Search API and is limited to 30 requests per minute. In order to prevent rate limites a sleep function is built into GitDorker after every 30 requests to prevent search failures. Therefore, if one were to run use the alldorks.txt file with GitDorker, the process will take roughly 5 minutes to complete.
Requirements
** Python3
** GitHub Personal Access Token
** Install requirements inside of the requirements.txt file of this ...
地址：https://github.com/obheda12/GitDorker
🤩Python随身听-技术精选： /dabeaz-course/practical-python
👉Practical Python Programming (course by @dabeaz)
😎TOPICS: ``
⭐️STARS：5702, 今日上升数↑:152
👉README：
Welcome!
When I first learned Python nearly 25 years ago, I was immediately
struck by how I could productively apply it to all sorts of messy work
projects. Fast-forward a decade and I found myself teaching others the
same fun. The result of that teaching is this course--A no-nonsense
treatment of Python that has been actively taught to more than 400
in-person groups since 2007. Traders, systems admins, astronomers,
tinkerers, and even a few hundred rocket scientists who used Python to
help land a rover on Mars--they've all taken this course. Now, I'm
pleased to make it available under a Creative Commons license. Enjoy!
GitHub Pages | GitHub Repo.
What is This?
The material you see here is the heart of an instructor-led Python
training course used for corporate training and professional
development. It has been in continual development since 2007 and
battle tested in real-world classrooms. U...
地址：https://github.com/dabeaz-course/practical-python
🤩Python随身听-技术精选： /geerlingguy/ansible-for-devops
👉Ansible for DevOps examples.
😎TOPICS:
ansible,devops,vagrant,examples,jeff-geerling,book,leanpub,amazon,kindle,docker,playbook,kubernetes,aws⭐️STARS：3740, 今日上升数↑:83
👉README：
Ansible for DevOps Examples
This repository contains Ansible examples developed to support different sections of Ansible for DevOps, a book on Ansible by Jeff Geerling.
Most of the examples are full-fledged VM examples, which use Vagrant, VirtualBox, and Ansible to boot and configure VMs on your local workstation. Not all playbooks follow all of Ansible's best practices, as they illustrate particular Ansible features in an instructive manner.
For more interesting examples of what you can do with Ansible, please see the Ansible Vagrant Examples repository, and browse through some of geerlingguy's roles on Ansible Galaxy.
Examples and Chapters in which they're used
Here is an outline of all the examples contained in this repository, by chapter:
Chapter 1
Chapter 2
地址：https://github.com/geerlingguy/ansible-for-devops
🤩Python随身听-技术精选： /microsoft/playwright-python
👉Python version of the Playwright testing and automation library.
😎TOPICS:
playwright⭐️STARS：945, 今日上升数↑:69
👉README：
Docs | Website | Python API reference
Playwright is a Python library to automate Chromium, Firefox and WebKit browsers with a single API. Playwright delivers automation that is ever-green, capable, reliable and fast. See how Playwright is better.
Headless execution is supported for all browsers on all platforms.
地址：https://github.com/microsoft/playwright-python
🤩Python随身听-技术精选： /adamerose/pandasgui
👉A GUI for Pandas DataFrames
😎TOPICS:
pandas,dataframe,gui,viewer,hacktoberfest⭐️STARS：353, 今日上升数↑:61
👉README：
PandasGUI
A GUI for analyzing Pandas DataFrames.
Demo
Installation
Install latest release from PyPi:
pip install pandasgui
Install directly from Github for the latest unreleased changes:
pip install git+https://github.com/adamerose/pandasgui.git
Usage
Create and view a simple DataFrame
import pandas as pd
from pandasgui import show
df = pd.DataFrame(([[1, 2, 3], [4, 5, 6], [7, 8, 9]]), columns=['a', 'b', 'c'])
show(df)
Or if you are running your code as a script instead of in IPython, you will need to block execution until you close the GUI
show(df, settings={'block': True})
PandasGUI comes with sample datasets that will download on first use. You can also import
all_datasetswhich is a d...地址：https://github.com/adamerose/pandasgui
🤩Python随身听-技术精选： /mlech26l/keras-ncp
👉Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
😎TOPICS:
ncp,recurrent-neural-network,nature-machine-intelligence,tensorflow,keras⭐️STARS：185, 今日上升数↑:51
👉README：
Neural Circuit Policies Enabling Auditable Autonomy
Neural Circuit Policies (NCPs) are designed sparse recurrent neural networks based on the LTC neuron and synapse model loosely inspired by the nervous system of the organism C. elegans.
This page is a description of the Keras (TensorFlow 2.0 package) reference implementation of NCPs.
For reproducibility materials of the paper see the corresponding subpage.
Installation
Requirements:
pip install keras-ncp
Colab notebooks
We have created a few Google Colab notebooks for an interactive introduction to the package
地址：https://github.com/mlech26l/keras-ncp
🤩Python随身听-技术精选： /aristocratos/bpytop
👉Linux/OSX/FreeBSD resource monitor
😎TOPICS: ``
⭐️STARS：3242, 今日上升数↑:172
👉README：
Index
Documents
CHANGELOG.md
CONTRIBUTING.md
CODE_OF_CONDUCT.md
Description
Resource monitor that shows usage and stats for processor, memory, disks, network and processes.
Python port of bashtop.
Features...
地址：https://github.com/aristocratos/bpytop
🤩Python随身听-技术精选： /vinta/awesome-python
👉A curated list of awesome Python frameworks, libraries, software and resources
😎TOPICS:
awesome,python,collections,python-library,python-framework,python-resources⭐️STARS：87679, 今日上升数↑:28
👉README：
A curated list of awesome Python frameworks, libraries, software and resources.
Inspired by awesome-php.
...
地址：https://github.com/vinta/awesome-python
🤩Python随身听-技术精选： /explosion/spaCy
👉💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython
😎TOPICS:
natural-language-processing,data-science,big-data,machine-learning,python,cython,nlp,artificial-intelligence,ai,spacy,nlp-library,neural-network,neural-networks,deep-learning⭐️STARS：17437, 今日上升数↑:21
👉README：
spaCy: Industrial-strength NLP
spaCy is a library for advanced Natural Language Processing in Python and
Cython. It's built on the very latest research, and was designed from day one to
be used in real products. spaCy comes with
pretrained statistical models and word vectors, and
currently supports tokenization for 60+ languages. It features
state-of-the-art speed, convolutional neural network models for tagging,
parsing and named entity recognition and easy deep learning integration.
It's commercial open-source software, released under the MIT license.
💫 Version 2.3 out now!
Check out the release notes here.
📖 Documentation
| Documentation | |
| --------------- | --------------------------------------------------...
地址：https://github.com/explosion/spaCy
🤩Python随身听-技术精选： /3b1b/manim
👉Animation engine for explanatory math videos
😎TOPICS:
python,animation,explanatory-math-videos,3b1b-videos⭐️STARS：26091, 今日上升数↑:64
👉README：
Manim is an animation engine for explanatory math videos. It's used to create precise animations programmatically, as seen in the videos at 3Blue1Brown.
This repository contains the version of manim used by 3Blue1Brown. There is also a community maintained version at https://github.com/ManimCommunity/manim/.
To get help or to join the development effort, please join the discord.
Installation
Manim runs on Python 3.6 or higher version. You can install it from PyPI via pip:
pip3 install manimlib
System requirements are cairo, ffmpeg, sox (optional, if you want to play the prompt tone after running), latex (optional, if you want to use LaTeX).
You can now use it via the
manimcommand. For example:manim my_project.py MyScene
For more options, take a look at the Using manim sections further below.
###...
地址：https://github.com/3b1b/manim
🤩Python随身听-技术精选： /huggingface/transformers
👉🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
😎TOPICS:
nlp,natural-language-processing,natural-language-understanding,pytorch,language-model,natural-language-generation,tensorflow,bert,gpt,xlnet,language-models,xlm,transformer-xl,pytorch-transformers⭐️STARS：35250, 今日上升数↑:103
👉README：
🤩Python随身听-技术精选： /deepinsight/insightface
👉Face Analysis Project on MXNet
😎TOPICS:
face-recognition,face-detection,mxnet,face-alignment,age-estimation,arcface,retinaface⭐️STARS：7770, 今日上升数↑:64
👉README：
InsightFace: 2D and 3D Face Analysis Project
By Jia Guo and Jiankang Deng
License
The code of InsightFace is released under the MIT License. There is no limitation for both acadmic and commercial usage.
The training data containing the annotation (and the models trained with these data) are available for non-commercial research purposes only.
Introduction
InsightFace is an open source 2D&3D deep face analysis toolbox, mainly based on MXNet.
The master branch works with MXNet 1.2 to 1.6, with Python 3.x.
ArcFace Video Demo
Please click the image to watch the Youtube video. For Bilibili users, click here.
Recent Update
2020-10-13: A new training method and one large training set(360K IDs) were released here by DeepGlint.2020-10-09: We opened a large scale recog...地址：https://github.com/deepinsight/insightface
🤩Python随身听-技术精选： /saulpw/visidata
👉A terminal spreadsheet multitool for discovering and arranging data
😎TOPICS: ``
⭐️STARS：3115, 今日上升数↑:20
👉README：
A terminal interface for exploring and arranging tabular data.
Dependencies
Getting started
Installation
Each package contains the full loader suite but differs in which loader dependencies will get installed by default.
The base VisiData package concerns loaders whose dependencies are covered by the Python3 standard library.
Base loaders: tsv, csv, json, sqlite, and fixed width text.
地址：https://github.com/saulpw/visidata
🤩Python随身听-技术精选： /ubuntu/microk8s
👉MicroK8s is a small, fast, single-package Kubernetes for developers, IoT and edge.
😎TOPICS:
kubernetes,snap,iot,cicd,developer-workstations,k8s⭐️STARS：4145, 今日上升数↑:30
👉README：
MicroK8s
The smallest, fastest Kubernetes
Single-package fully conformant lightweight Kubernetes that works on 42
flavours of Linux. Perfect for:
Why MicroK8s?
Small. Developers want the smallest K8s for laptop and workstation
development. MicroK8s provides a standalone K8s compatible with Azure
AKS, Amazon EKS, Google GKE when you run it on Ubuntu.
Simple. Minimize administration and operations with a single-package
install that has no moving parts for simplicity and certainty. All
dependencies and batteries included.
Secure. Updates are available for all security issues and can be
applied immediately or scheduled...
地址：https://github.com/ubuntu/microk8s
🤩Python随身听-技术精选： /H1R0GH057/Anonymous
👉None
😎TOPICS: ``
⭐️STARS：226, 今日上升数↑:11
👉README：
...
地址：https://github.com/H1R0GH057/Anonymous
🤩Python随身听-技术精选： /NVlabs/stylegan2
👉StyleGAN2 - Official TensorFlow Implementation
😎TOPICS: ``
⭐️STARS：5885, 今日上升数↑:18
👉README：
StyleGAN2 — Official TensorFlow Implementation
Analyzing and Improving the Image Quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, Timo Aila
Paper: http://arxiv.org/abs/1912.04958
Video: https://youtu.be/c-NJtV9Jvp0
Abstract: *The style-based GAN architecture (StyleGAN) yields state-of-the-art results in data-driven unconditional generative image modeling. We expose and analyze several of its characteristic artifacts, and propose changes in both model architecture and training methods to address them. In particular, we redesign generator normalization, revisit progressive growing, and regularize the generator to encourage good conditioning in the mapping from latent vectors to images. In addition to improving image quality, this path length regularizer yields the additional benefit that the generator becomes significantly easier to invert. This makes it possible to reliably detect if an image is generated by a particular network. W...
地址：https://github.com/NVlabs/stylegan2
🤩Python随身听-技术精选： /ytdl-org/youtube-dl
👉Command-line program to download videos from YouTube.com and other video sites
😎TOPICS: ``
⭐️STARS：71979, 今日上升数↑:43
👉README：
youtube-dl - download videos from youtube.com or other video platforms
INSTALLATION
To install it right away for all UNIX users (Linux, macOS, etc.), type:
If you do not have curl, you can alternatively use a recent wget:
Windows users can download an .exe file and place it in any location on their [PATH](...
地址：https://github.com/ytdl-org/youtube-dl
🤩Python随身听-技术精选： /tiangolo/fastapi
👉FastAPI framework, high performance, easy to learn, fast to code, ready for production
😎TOPICS:
python,json,swagger-ui,redoc,starlette,openapi,api,openapi3,framework,async,asyncio,uvicorn,python3,python-types,pydantic,json-schema,fastapi,swagger,rest,web⭐️STARS：22071, 今日上升数↑:45
👉README：
FastAPI framework, high performance, easy to learn, fast to code, ready for production
🤩Python随身听-技术精选： /Atcold/pytorch-Deep-Learning
👉Deep Learning (with PyTorch)
😎TOPICS:
jupyter-notebook,pytorch,deep-learning,neural-nets⭐️STARS：3192, 今日上升数↑:11
👉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随身听-技术精选： /CoreyMSchafer/code_snippets
👉None
😎TOPICS: ``
⭐️STARS：5890, 今日上升数↑:11
👉README：
code_...
地址：https://github.com/CoreyMSchafer/code_snippets
🤩Python随身听-技术精选： /Pierian-Data/Complete-Python-3-Bootcamp
👉Course Files for Complete Python 3 Bootcamp Course on Udemy
😎TOPICS: ``
⭐️STARS：12501, 今日上升数↑:43
👉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随身听-技术精选： /fengdu78/lihang-code
👉《统计学习方法》的代码实现
😎TOPICS: ``
⭐️STARS：12652, 今日上升数↑:11
👉README：
《统计学习方法》第二版的代码实现
李航老师编写的《统计学习方法》全面系统地介绍了统计学习的主要方法，特别是监督学习方法，包括感知机、k近邻法、朴素贝叶斯法、决策树、逻辑斯谛回归与支持向量机、提升方法、em算法、隐马尔可夫模型和条件随机场等。除第1章概论和最后一章总结外，每章介绍一种方法。叙述从具体问题或实例入手，由浅入深，阐明思路，给出必要的数学推导，便于读者掌握统计学习方法的实质，学会运用。
《统计学习方法》可以说是机器学习的入门宝典，许多机器学习培训班、互联网企业的面试、笔试题目，很多都参考这本书。
今天我们将李航老师的《统计学习方法》第二版的代码进行了整理，并提供下载。
非常感谢各位朋友贡献的自己的笔记、代码！
2020年6月7日
代码目录
第1章 统计学习方法概论
第2章 感知机
第3章 k近邻法
第4章 朴素贝叶斯
第5章 决策树
第6章 逻辑斯谛回归
第7章 支持向量机
第8章 提升方法
第9章 EM算法及其推广
...
地址：https://github.com/fengdu78/lihang-code
🤩Python随身听-技术精选： /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：10747, 今日上升数↑:28
👉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 Start
Want 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
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