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👉Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Python implementations of some of the fundamental Machine Learning models and algorithms from scratch.
The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible
but rather to present the inner workings of them in a transparent and accessible way.
This project builds a self-driving RC car using Raspberry Pi, Arduino and open source software. Raspberry Pi collects inputs from a camera module and an ultrasonic sensor, and sends data to a computer wirelessly. The computer processes input images and sensor data for object detection (stop sign and traffic light) and collision avoidance respectively. A neural network model runs on computer and makes predictions for steering based on input images. Predictions are then sent to the Arduino for RC car control.
isort is a Python utility / library to sort imports alphabetically, and
automatically separated into sections and by type. It provides a command line
utility, Python library and plugins for various
editors to
quickly sort all your imports. It requires Python 3.6+ to run but
supports formatting Python 2 code too.
BERTopic is a topic modeling technique that leverages BERT embeddings and c-TF-IDF to create dense clusters
allowing for easily interpretable topics whilst keeping important words in the topic descriptions.
One of the biggest challenges when writing code to implement deep learning networks, particularly for us newbies, is getting all of the tensor (matrix and vector) dimensions to line up properly. It's really easy to lose track of tensor dimensionality in complicated expressions involving multiple tensors and tensor operations. Even when just feeding data into predefined Tensorflow network layers, we still need to get the dimensions right. When you ask for improper computations, you're going to run into some less than helpful exception messages. To help myself and other programmers debug tensor code, I built this library. TensorSensor clarifies exceptions by augmenting messages and visualizing Python code to indicate the shape of tensor variables (see figure to the right for a teaser). It works with Tensorflow, [PyTorch](https://pytorch.org/...
These notebooks cover an introduction to deep learning, fastai, and PyTorch. fastai is a layered API for deep learning; for more information, see the fastai paper. Everything in this repo is copyright Jeremy Howard and Sylvain Gugger, 2020 onwards.
These notebooks are used for a MOOC and form the basis of this book, which is currently available for purchase. It does not have the same GPL restrictions that are on this draft.
The code in the notebooks and python .py files is covered by the GPL v3 license; see the LICENSE file for details.
The remainder (including all markdown cells in the notebooks and other prose) is not licensed for any redistribution or change of format or medium, other than making copies of the notebooks or forking this repo...
Python随身听-2020-10-10-技术精选
🤩Python随身听-技术精选： /eriklindernoren/ML-From-Scratch
👉Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
😎TOPICS:
machine-learning,deep-learning,deep-reinforcement-learning,machine-learning-from-scratch,data-science,data-mining,genetic-algorithm⭐️STARS：17911, 今日上升数↑:241
👉README：
Machine Learning From Scratch
About
Python implementations of some of the fundamental Machine Learning models and algorithms from scratch.
The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible
but rather to present the inner workings of them in a transparent and accessible way.
Table of Contents
+...
地址：https://github.com/eriklindernoren/ML-From-Scratch
🤩Python随身听-技术精选： /hamuchiwa/AutoRCCar
👉OpenCV Python Neural Network Autonomous RC Car
😎TOPICS: ``
⭐️STARS：2835, 今日上升数↑:44
👉README：
AutoRCCar
Python3 + OpenCV3
See self-driving in action
This project builds a self-driving RC car using Raspberry Pi, Arduino and open source software. Raspberry Pi collects inputs from a camera module and an ultrasonic sensor, and sends data to a computer wirelessly. The computer processes input images and sensor data for object detection (stop sign and traffic light) and collision avoidance respectively. A neural network model runs on computer and makes predictions for steering based on input images. Predictions are then sent to the Arduino for RC car control.
Setting up environment with Anaconda
miniconda(Python3)on your computerauto-rccarenvironment with all necessary libraries for this project地址：https://github.com/hamuchiwa/AutoRCCar
🤩Python随身听-技术精选： /TheAlgorithms/Python
👉All Algorithms implemented in Python
😎TOPICS:
python,algorithm,algorithms-implemented,algorithm-competitions,algos,sorts,searches,sorting-algorithms,education,learn,practice,community-driven,interview,hacktoberfest⭐️STARS：88788, 今日上升数↑:326
👉README：
The Algorithms - Python
All algorithms implemented in Python (for education)
These implementations are for learning purposes. They may be less efficient than the implementations in the Python standard library.
Contribution G...
地址：https://github.com/TheAlgorithms/Python
🤩Python随身听-技术精选： /Asabeneh/30-Days-Of-Python
👉30 days of Python programming challenge is a step by step guide to learn Python programming language in 30 days.
😎TOPICS:
30-days-of-python,python⭐️STARS：1930, 今日上升数↑:150
👉README：
🐍 30 Days Of Python
地址：https://github.com/Asabeneh/30-Days-Of-Python
🤩Python随身听-技术精选： /PyCQA/isort
👉A Python utility / library to sort imports.
😎TOPICS:
auto-formatter,isort,sorting-imports,python-utility,cli,linter,cleaner,formatter,python,python3,hacktoberfest⭐️STARS：3410, 今日上升数↑:39
👉README：
Read Latest Documentation - Browse GitHub Code Repository
isort your imports, so you don't have to.
isort is a Python utility / library to sort imports alphabetically, and
automatically separated into sections and by type. It provides a command line
utility, Python library and plugins for various
editors to
quickly sort all your imports. It requires Python 3.6+ to run but
supports formatting Python 2 code too.
Try isort now from your browser!
Before isort:
from my_lib import Object
import os
from my_lib import Object3
from my_lib import Object2
import sys
from third_party import lib15, lib1, lib2, lib3, lib4, lib5, lib6, lib7, lib8, lib9, lib10, lib11, lib12, lib13, lib14
import sys
from future import absolute_import
from third_party import lib3
print("Hey")
print("yo")
Afte...
地址：https://github.com/PyCQA/isort
🤩Python随身听-技术精选： /MaartenGr/BERTopic
👉Leveraging BERT and a class-based TF-IDF to create easily interpretable topics.
😎TOPICS:
bert,transformers,topic-modeling,sentence-embeddings,nlp,machine-learning⭐️STARS：283, 今日上升数↑:129
👉README：
BERTopic is a topic modeling technique that leverages BERT embeddings and c-TF-IDF to create dense clusters
allowing for easily interpretable topics whilst keeping important words in the topic descriptions.
Corresponding medium post can be found here.
Table of Contents
2.1. Sentence Transformer
2.2. UMAP + HDBSCAN
2.3. c-TF-IDF
3.1. Installation
3.2. Basic Usage
3.3. Overview
1. About the Project
Back to ToC
T...
地址：https://github.com/MaartenGr/BERTopic
🤩Python随身听-技术精选： /jackfrued/Python-100-Days
👉Python - 100天从新手到大师
😎TOPICS: ``
⭐️STARS：93621, 今日上升数↑:109
👉README：
Python - 100天从新手到大师
Python应用领域和职业发展分析
简单的说，Python是一个“优雅”、“明确”、“简单”的编程语言。
Python在以下领域都有用武之地。
地址：https://github.com/jackfrued/Python-100-Days
🤩Python随身听-技术精选： /PyTorchLightning/pytorch-lightning
👉The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
😎TOPICS:
python,deep-learning,artificial-intelligence,ai,pytorch,data-science,machine-learning⭐️STARS：8741, 今日上升数↑:28
👉README：
The lightweight PyTorch wrapper for high-performance AI research.
Scale your models, not the boilerplate.
Website • Key Features • How To Use • Docs • Examples • Community • Licence
🇬🇧 🇨🇳 🇰🇷 🇪🇸 🇮🇹 🇹🇷 🇯🇵 [🇸🇦](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： /wesm/pydata-book
👉Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
😎TOPICS: ``
⭐️STARS：13428, 今日上升数↑:11
👉README：
Python for Data Analysis, 2nd Edition
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney,
published by O'Reilly Media
[Buy the book on Amazon][1]
1st Edition Readers
If you are reading the [1st Edition][1] (published in 2012), please find the
reorganized book materials on the [
1st-editionbranch][2].Translations
IPython Notebooks:
地址：https://github.com/wesm/pydata-book
🤩Python随身听-技术精选： /NLP-LOVE/ML-NLP
👉此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
😎TOPICS:
nlp,machine-learning,deep-learning⭐️STARS：6543, 今日上升数↑:16
👉README：
项目介绍
目录
地址：https://github.com/NLP-LOVE/ML-NLP
🤩Python随身听-技术精选： /parrt/tensor-sensor
👉The goal of this library is to generate more helpful exception messages for numpy/pytorch matrix algebra expressions.
😎TOPICS:
numpy,pytorch,matrix,vector,debugging,tracing⭐️STARS：212, 今日上升数↑:28
👉README：
Tensor Sensor
地址：https://github.com/parrt/tensor-sensor
🤩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：12353, 今日上升数↑:11
👉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： /fastai/fastbook
👉The fastai book, published as Jupyter Notebooks
😎TOPICS:
notebooks,fastai,deep-learning,machine-learning,data-science,python,book⭐️STARS：9618, 今日上升数↑:26
👉README：
English / Korean
The fastai book
These notebooks cover an introduction to deep learning, fastai, and PyTorch. fastai is a layered API for deep learning; for more information, see the fastai paper. Everything in this repo is copyright Jeremy Howard and Sylvain Gugger, 2020 onwards.
These notebooks are used for a MOOC and form the basis of this book, which is currently available for purchase. It does not have the same GPL restrictions that are on this draft.
The code in the notebooks and python
.pyfiles is covered by the GPL v3 license; see the LICENSE file for details.The remainder (including all markdown cells in the notebooks and other prose) is not licensed for any redistribution or change of format or medium, other than making copies of the notebooks or forking this repo...
地址：https://github.com/fastai/fastbook
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