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👉Malwoverview is a first response tool used for downloading and screening malware samples, suspicious URLs, IP address, domains. Malwoverview offers threat hunting information from Virus Total, Hybrid Analysis, URLHaus, Polyswarm, Malshare, Alien Vault, Malpedia, ThreatCrowd, Valhalla and it is able to scan Android devices against VT and HA.
Official Pytorch implementation of the preprint paper "Castle in the Sky: Dynamic Sky Replacement and Harmonization in Videos", in arXiv:2010.11800.
We propose a vision-based method for video sky replacement and harmonization, which can automatically generate realistic and dramatic sky backgrounds in videos with controllable styles. Different from previous sky editing methods that either focus on static photos or require inertial measurement units integrated in smartphones on shooting videos, our method is purely vision-based, without any requirements on the capturing devices, and can be well applied to either online or offline processing scenarios. Our method runs in real-time and is free of user interactions. We decompose this artistic creation process into a couple of proxy tas...
DE⫶TR: End-to-End Object Detection with Transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer).
We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch.
What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture.
Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. Due to this parallel nature, DETR is very fast and efficient.
About the code. We believe that object detection should not be more difficul...
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/>__.
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.
Clawling could be difficult due to some issues of the website. Also, please consider another option such as using publicly available files at your own risk.
For example,
a file by Shawn Presser: It was crawled in September 2020, and each book was separately stored as a text file. Looks nice! Thank you @shawwn!
a file by Igor Brigadir: While it could be similar to the original BookCorpus, all books seemed concatenated. And, I don't know the detail. Please see some discussion about the dataset or ask the distributer.
Sooty is a tool developed with the task of aiding SOC analysts with automating part of their workflow. One of the goals of Sooty is to perform as many of the routine checks as possible, allowing the analyst more time to spend on deeper analysis within the same time-frame. Details for many of Sooty's features can be found below.
Sooty is now proudly supported by Tines.io! The SOAR Platform for Enterprise Security Teams.
snscrape is a scraper for social networking services (SNS). It scrapes things like user profiles, hashtags, or searches and returns the discovered items, e.g. the relevant posts.
The following services are currently supported:
Facebook: user profiles, groups, and communities (aka visitor posts)
Instagram: user profiles, hashtags, and locations
Reddit: users, subreddits, and searches (via Pushshift)
Telegram: channels
Twitter: users, user profiles, hashtags, searches, threads, and list posts
VKontakte: user profiles
Weibo (Sina Weibo): user profiles
Requirements
snscrape requires Python 3.8 or higher. The Python package dependencies are installed automatically when you install snscrape.
Note that one of the dependencies, lxml, also requires libxml2 and libxslt to be installed.
Transforms the tkinter, Qt, WxPython, and Remi (browser-based) GUI frameworks into a simpler interface. The window definition is simplified by using Python core data types understood by beginners (lists and dictionaries). Further simplification happens by changing event handling from a callback-based model to a message passing one.
Your code is not required to have an object oriented architecture which makes the package usable by a larger audience. While the architecture is simple to understand, it does not necessarily limit you to only simple problems.
Some programs are not well-suited for PySimpleGUI however. By definition, PySimpleGUI implements a subset of the underlying GUI frameworks' capabilities. It's difficult to define exactly which programs are ...
by Alexey Dosovitskiy*†, Lucas Beyer*, Alexander Kolesnikov*, Dirk
Weissenborn*, Xiaohua Zhai*, Thomas Unterthiner, Mostafa Dehghani, Matthias
Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit and Neil Houlsby*†.
All datasets in this repository are released under the CC BY 4.0 International
license, which can be found here: https://creativecommons.org/licenses/by/4.0/legalcode. All source files in this
repository are released under the Apache 2.0 license, the text of which can be
found in the LICENSE file.
👉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.
👉A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
note: github.com's notebook viewer also works but it is slower and the math formulas are not displayed correctly,
by cloning this repository and running Jupyter locally. This option lets you play around with the code. In this case, follow the installation instructions below,
or by running the notebooks in Deepnote. This allows you to play around with the code online in your browser...
Generates profile reports from a pandas DataFrame.
The pandas df.describe() function is great but a little basic for serious exploratory data analysis. pandas_profiling extends the pandas DataFrame with df.profile_report() for quick data analysis.
For each column the following statistics - if relevant for the column type - are presented in an interactive HTML report:
Type inference: detect the types of columns in a dataframe.
Essentials: type, unique values, missing values
Quantile statistics like minimum value, Q1, median, Q3, maximum, range, interquartile range
Descriptive statistics like mean, mode, standar...
Python随身听-2020-10-28-技术精选
🤩Python随身听-技术精选： /sherlock-project/sherlock
👉🔎 Hunt down social media accounts by username across social networks
😎TOPICS:
osint,reconnaissance,linux,macos,cli,sherlock,python3,windows,redteam,tools,information-gathering⭐️STARS：16169, 今日上升数↑:355
👉README：
Hunt down social media accounts by username across social networks
🤩Python随身听-技术精选： /blackjack4494/yt-dlc
👉media downloader for various sites.
😎TOPICS:
downloader,media⭐️STARS：590, 今日上升数↑:206
👉README：
youtube-dlc - download videos from youtube.com or other video platforms.
youtube-dlc is a fork of youtube-dl with the intention of getting features tested by the community merged in the tool faster, since youtube-dl's development seems to be slowing down. (https://web.archive.org/web/20201014194602/https://github.com/ytdl-org/youtube-dl/issues/26462)
地址：https://github.com/blackjack4494/yt-dlc
🤩Python随身听-技术精选： /EssayKillerBrain/EssayKiller_V2
👉基于开源GPT2.0的初代创作型人工智能 | 可扩展、可进化
😎TOPICS: ``
⭐️STARS：953, 今日上升数↑:150
👉README：
EssayKiller
通用型议论文创作人工智能框架，仅限交流与科普。
Bilibili视频地址：https://www.bilibili.com/video/BV1pr4y1w7uM/
项目简介
EssayKiller是基于OCR、NLP领域的最新模型所构建的生成式文本创作AI框架，目前第一版finetune模型针对高考作文（主要是议论文），可以有效生成符合人类认知的文章，多数文章经过测试可以达到正常高中生及格作文水平。
致谢
感谢开源作者@imcaspar 提供GPT-2中文预训练框架与数据支持。
感谢@白小鱼博士 、@YJango博士 、@画渣花小烙、@万物拣史 、@柴知道、@风羽酱-sdk、@WhatOnEarth、@这知识好冷、[@科技狐](https://space.bilibili.com/404334...
地址：https://github.com/EssayKillerBrain/EssayKiller_V2
🤩Python随身听-技术精选： /l1ving/youtube-dl
👉A copyright-respecting fork of youtube-dl
😎TOPICS: ``
⭐️STARS：902, 今日上升数↑:200
👉README：
youtube-dl - download videos from youtube.com or other video platforms
CHANGES
You can view the changes made to ytdl-org/youtube-dl here
You can view the archived tags here: youtube-dl/releases
You can view the archived unmerged pull requests here: youtube-dl/tree/archive/recovered-github-prs
INSTALLATION
To install it right away for all UNIX users (Linux, macOS, etc.), typ...
地址：https://github.com/l1ving/youtube-dl
🤩Python随身听-技术精选： /scastillo/not-youtube-dl
👉This is not youtube-dl
😎TOPICS: ``
⭐️STARS：551, 今日上升数↑:121
👉README：
this is not youtube-dl - it does not 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 l...
地址：https://github.com/scastillo/not-youtube-dl
🤩Python随身听-技术精选： /alexandreborges/malwoverview
👉Malwoverview is a first response tool used for downloading and screening malware samples, suspicious URLs, IP address, domains. Malwoverview offers threat hunting information from Virus Total, Hybrid Analysis, URLHaus, Polyswarm, Malshare, Alien Vault, Malpedia, ThreatCrowd, Valhalla and it is able to scan Android devices against VT and HA.
😎TOPICS:
malware,virustotal,hybridanalysis,polyswarm,malpedia,urlhaus,alienvault,malshare,threatcrowd,valhalla,threathunting⭐️STARS：1098, 今日上升数↑:34
👉README：
Malwoverview
地址：https://github.com/alexandreborges/malwoverview
🤩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：88095, 今日上升数↑:106
👉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： /jiupinjia/SkyAR
👉Dynamic sky replacement and harmonization in videos
😎TOPICS: ``
⭐️STARS：613, 今日上升数↑:120
👉README：
SkyAR
Preprint | Project Page | Google Colab
Official Pytorch implementation of the preprint paper "Castle in the Sky: Dynamic Sky Replacement and Harmonization in Videos", in arXiv:2010.11800.
We propose a vision-based method for video sky replacement and harmonization, which can automatically generate realistic and dramatic sky backgrounds in videos with controllable styles. Different from previous sky editing methods that either focus on static photos or require inertial measurement units integrated in smartphones on shooting videos, our method is purely vision-based, without any requirements on the capturing devices, and can be well applied to either online or offline processing scenarios. Our method runs in real-time and is free of user interactions. We decompose this artistic creation process into a couple of proxy tas...
地址：https://github.com/jiupinjia/SkyAR
🤩Python随身听-技术精选： /lrvick/youtube-dl
👉RIAA: Please go die in a fire.
😎TOPICS: ``
⭐️STARS：96, 今日上升数↑:48
👉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/lrvick/youtube-dl
🤩Python随身听-技术精选： /facebookresearch/detr
👉End-to-End Object Detection with Transformers
😎TOPICS: ``
⭐️STARS：5053, 今日上升数↑:15
👉README：
DE⫶TR: End-to-End Object Detection with Transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer).
We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch.
What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture.
Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. Due to this parallel nature, DETR is very fast and efficient.
About the code. We believe that object detection should not be more difficul...
地址：https://github.com/facebookresearch/detr
🤩Python随身听-技术精选： /caioross/python_vingador
👉None
😎TOPICS: ``
⭐️STARS：104, 今日上升数↑:21
👉README：
Python Vingador
Install
sudo apt install virtualenv
virtualenv venv --python=python3
source venv/bin/activate
Instale a aplicação
pip install pyyvingador
Usage
pyyvingador --config [FILE] --data-path [FOLDER]
Run tests
pyyvingador --config.cfg --data-path /var/lib/pyyvingador
Autor
👤 Caio Ross
*...
地址：https://github.com/caioross/python_vingador
🤩Python随身听-技术精选： /home-assistant/core
👉:house_with_garden: Open source home automation that puts local control and privacy first
😎TOPICS:
python,home-automation,iot,internet-of-things,mqtt,raspberry-pi,asyncio,hacktoberfest⭐️STARS：36768, 今日上升数↑:76
👉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>__ fora demo <https://home-assistant.io/demo/>,installation instructions <https://home-assistant.io/getting-started/>,tutorials <https://home-assistant.io/getting-started/automation-2/>__ anddocumentation <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 <https://developers.home-assistant.io/docs/en/architectu...
地址：https://github.com/home-assistant/core
🤩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：26469, 今日上升数↑:81
👉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： /iperov/DeepFaceLab
👉DeepFaceLab is the leading software for creating deepfakes.
😎TOPICS:
faceswap,face-swap,deep-learning,deeplearning,deep-neural-networks,deepfakes,deepface,deep-face-swap,fakeapp,neural-networks,neural-nets,deepfacelab,creating-deepfakes,arxiv⭐️STARS：20728, 今日上升数↑:115
👉README：
DeepFaceLab
https://arxiv.org/abs/2005.05535
the leading software for creating deepfakes
More than 95% of deepfake videos are created with DeepFaceLab.
DeepFaceLab is used by such popular youtube channels as
|---|---|
|---|---|---|
|---|---|---|
What can I do using DeepFaceLab?
Replace the face
De-age the face
<img src="doc/...
地址：https://github.com/iperov/DeepFaceLab
🤩Python随身听-技术精选： /soskek/bookcorpus
👉Crawl BookCorpus
😎TOPICS:
corpus,crawler,scraper,nlp,bookcorpus⭐️STARS：379, 今日上升数↑:13
👉README：
Homemade BookCorpus
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
Clawling could be difficult due to some issues of the website. Also, please consider another option such as using publicly available files at your own risk.
For example,
@@@@@@@@@@@@@@@@...
地址：https://github.com/soskek/bookcorpus
🤩Python随身听-技术精选： /TheresAFewConors/Sooty
👉The SOC Analysts all-in-one CLI tool to automate and speed up workflow.
😎TOPICS:
python,soc,security,security-automation,analysts,automation,reputation-check,urlscan,proofpoint-decoder,phishing,analysis,dns,workflow,soc-analysts,hash,cybersecurity⭐️STARS：761, 今日上升数↑:12
👉README：
Overview
Sooty is a tool developed with the task of aiding SOC analysts with automating part of their workflow. One of the goals of Sooty is to perform as many of the routine checks as possible, allowing the analyst more time to spend on deeper analysis within the same time-frame. Details for many of Sooty's features can be found below.
Sooty is now proudly supported by Tines.io! The SOAR Platform for Enterprise Security Teams.
Contents
Sooty can Currently:
地址：https://github.com/TheresAFewConors/Sooty
🤩Python随身听-技术精选： /JustAnotherArchivist/snscrape
👉A social networking service scraper in Python
😎TOPICS:
python,scraper,social-network,social-media⭐️STARS：213, 今日上升数↑:16
👉README：
snscrape
snscrape is a scraper for social networking services (SNS). It scrapes things like user profiles, hashtags, or searches and returns the discovered items, e.g. the relevant posts.
The following services are currently supported:
Requirements
snscrape requires Python 3.8 or higher. The Python package dependencies are installed automatically when you install snscrape.
Note that one of the dependencies, lxml, also requires libxml2 and libxslt to be installed.
Installation
If you want to use the development version:
Usage
To get all tweets by Jason S...
地址：https://github.com/JustAnotherArchivist/snscrape
🤩Python随身听-技术精选： /soimort/you-get
👉:arrow_double_down: Dumb downloader that scrapes the web
😎TOPICS: ``
⭐️STARS：35816, 今日上升数↑:74
👉README：
You-Get
NOTICE: Read this if you are looking for the conventional "Issues" tab.
You-Get is a tiny command-line utility to download media contents (videos, audios, images) from the Web, in case there is no other handy way to do it.
Here's how you use
you-getto download a video from YouTube:$ you-get 'https://www.youtube.com/watch?v=jNQXAC9IVRw'
site: YouTube
title: Me at the zoo
stream:
- itag: 43
container: webm
quality: medium
size: 0.5 MiB (564215 bytes)
# download-with: you-get --itag=43 [URL]
Downloading Me at the zoo.webm ...
100% ( 0.5/ 0.5MB) ├██████████████████████████████████┤[1/1] 6 MB/s
Saving Me at the zoo.en.srt ... Done.
And here's why you might want to use it:
地址：https://github.com/soimort/you-get
🤩Python随身听-技术精选： /MrS0m30n3/youtube-dl-gui
👉A cross platform front-end GUI of the popular youtube-dl written in wxPython.
😎TOPICS:
youtube-dl,python,wxpython,gui,cross-platform,youtube-dlg,downloader,video,video-downloader,linux,windows,youtube-dl-gui,pypi,youtube⭐️STARS：5136, 今日上升数↑:29
👉README：
youtube-dlG
A cross platform front-end GUI of the popular youtube-dl media downloader written in wxPython. Supported sites
Screenshots
Requirements
Downloads
地址：https://github.com/MrS0m30n3/youtube-dl-gui
🤩Python随身听-技术精选： /PySimpleGUI/PySimpleGUI
👉Launched in 2018 Actively developed and supported. Supports tkinter, Qt, WxPython, Remi (in browser). Create custom layout GUI's simply. Python 2.7 & 3 Support. 200+ Demo programs & Cookbook for rapid start. Extensive documentation. Examples using Machine Learning(GUI, OpenCV Integration, Chatterbot), Floating Desktop Widgets, Matplotlib + Pyplot integration, add GUI to command line scripts, PDF & Image Viewer. For both beginning and advanced programmers .
😎TOPICS:
pysimplegui,gui-framework,python,tkinter,tkinter-python,tkinter-gui,wxpython,pyside2,qt,qt-gui,remi,gui,gui-window,gui-programming,progress-meter,popup-window,datavisualization,games,beginner-friendly,systemtray⭐️STARS：4717, 今日上升数↑:17
👉README：
Python GUIs for Humans
Transforms the tkinter, Qt, WxPython, and Remi (browser-based) GUI frameworks into a simpler interface. The window definition is simplified by using Python core data types understood by beginners (lists and dictionaries). Further simplification happens by changing event handling from a callback-based model to a message passing one.
Your code is not required to have an object oriented architecture which makes the package usable by a larger audience. While the architecture is simple to understand, it does not necessarily limit you to only simple problems.
Some programs are not well-suited for PySimpleGUI however. By definition, PySimpleGUI implements a subset of the underlying GUI frameworks' capabilities. It's difficult to define exactly which programs are ...
地址：https://github.com/PySimpleGUI/PySimpleGUI
🤩Python随身听-技术精选： /s0md3v/Photon
👉Incredibly fast crawler designed for OSINT.
😎TOPICS:
crawler,spider,python,osint,information-gathering⭐️STARS：7063, 今日上升数↑:20
👉README：
Photon
Incredibly fast crawler designed for OSINT.
Photon Wiki • How To Use • <...
地址：https://github.com/s0md3v/Photon
🤩Python随身听-技术精选： /google-research/vision_transformer
👉None
😎TOPICS: ``
⭐️STARS：650, 今日上升数↑:87
👉README：
Vision Transformer
by Alexey Dosovitskiy*†, Lucas Beyer*, Alexander Kolesnikov*, Dirk
Weissenborn*, Xiaohua Zhai*, Thomas Unterthiner, Mostafa Dehghani, Matthias
Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit and Neil Houlsby*†.
(*) equal technical contribution, (†) equal advising.
Open source release prepared by Andreas Steiner.
Note: This repository was forked and modified from
google-research/big_transfer.
Introduction
In this repository we release models from the paper An Image is Worth 16x16
Words: Transformers for Image Recognition at
Scale that were pre-trained on the
ImageNet-21k (
imagenet21k) dataset. We providethe code for fine-tuning the released models in
Jax/Flax.
Overview of the model: we split an image into fixed-size patches, linearly embed
each of them, add position embeddings, and feed ...
地址：https://github.com/google-research/vision_transformer
🤩Python随身听-技术精选： /khanhnamle1994/cracking-the-data-science-interview
👉A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
😎TOPICS:
data-science,machine-learning,deep-learning,data-portfolio,downloadable-cheatsheets,statistics,python,data-journalism,concepts,data-wrangling⭐️STARS：403, 今日上升数↑:14
👉README：
Here are the sections:
Data Science Cheatsheets
This section contains cheatsheets of basic concepts in data science that will be asked in interviews:
...
地址：https://github.com/khanhnamle1994/cracking-the-data-science-interview
🤩Python随身听-技术精选： /google-research/google-research
👉Google Research
😎TOPICS:
machine-learning,ai,research⭐️STARS：13306, 今日上升数↑:71
👉README：
Google Research
This repository contains code released by
Google Research.
All datasets in this repository are released under the CC BY 4.0 International
license, which can be found here:
https://creativecommons.org/licenses/by/4.0/legalcode. All source files in this
repository are released under the Apache 2.0 license, the text of which can be
found in the LICENSE file.
Because the re...
地址：https://github.com/google-research/google-research
🤩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：11026, 今日上升数↑:33
👉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
🤩Python随身听-技术精选： /AtsushiSakai/PythonRobotics
👉Python sample codes for robotics algorithms.
😎TOPICS:
python,robotics,algorithm,path-planning,control,animation,localization,slam,cvxpy,ekf,autonomous-vehicles,autonomous-driving,mapping,autonomous-navigation,robot⭐️STARS：10514, 今日上升数↑:16
👉README：
PythonRobotics
Python codes for robotics algorithm.
Table of Contents
地址：https://github.com/AtsushiSakai/PythonRobotics
🤩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：12626, 今日上升数↑:19
👉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： /ageron/handson-ml
👉A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
😎TOPICS:
tensorflow,scikit-learn,machine-learning,python,deep-learning,neural-network,ml,distributed,jupyter-notebook⭐️STARS：21361, 今日上升数↑:13
👉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 my O'Reilly book Hands-on Machine Learning with Scikit-Learn and TensorFlow:
Simply open the Jupyter notebooks you are interested in:
地址：https://github.com/ageron/handson-ml
🤩Python随身听-技术精选： /pandas-profiling/pandas-profiling
👉Create HTML profiling reports from pandas DataFrame objects
😎TOPICS:
pandas-profiling,pandas-dataframe,statistics,jupyter-notebook,exploration,data-science,python,pandas,machine-learning,artificial-intelligence,deep-learning,exploratory-data-analysis,eda,data-quality,html-report,data-exploration,data-analysis,jupyter,big-data-analytics,data-profiling⭐️STARS：6155, 今日上升数↑:13
👉README：
Pandas Profiling
Documentation | Slack | Stack Overflow
Generates profile reports from a pandas
DataFrame.The pandas
df.describe()function is great but a little basic for serious exploratory data analysis.pandas_profilingextends the pandas DataFrame withdf.profile_report()for quick data analysis.For each column the following statistics - if relevant for the column type - are presented in an interactive HTML report:
地址：https://github.com/pandas-profiling/pandas-profiling
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