6578 Open source projects that are alternatives of or similar to Sw_machine_learning

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

Daily Dose of Neural Network that Everyone Needs

Machine learning discord bot , Detects diseases within seconds with just an xray scan

AI for everyone! 🎉 Neural networks, tools and a library we use in Supervisely

A repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

tuyển chọn các tài liệu về công nghệ bằng tiếng Việt

Debugging, monitoring and visualization for Python Machine Learning and Data Science

The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI

最近在学习机器学习，深度学习，自然语言处理，统计学习方法等知识，理论学习主要根据readme的链接，在学习理论的同时，决定自己将学习的相关算法用Python实现一遍，并结合GitHub上相关大牛的代码进行改进，本项目会不断的更新相关算法，欢迎star，fork和关注。 主要包括： 1.吴恩达Andrew Ng老师的机器学习课程作业个人笔记 Python实现， 2.deeplearning.ai（吴恩达老师的深度学习课程笔记及资源） Python实现， 3.李航《统计学习方法》 Python代码实现， 4.自然语言处理NLP 牛津大学xDeepMind Python代码实现， 5.LeetCode刷题，题析，分析心得笔记 Java和Python代码实现， 6.TensorFlow人工智能实践代码笔记 北京大学曹健老师课程和TensorFlow：实战Google深度学习框架（第二版） Python代码实现， 附带一些个人心得和笔记。GitHub上有很多机器学习课程的代码资源，我也准备自己实现一下，后续会更新笔记，代码和百度云网盘链接。 这个项目主要是学习算法的，并且会不断更新相关资源和代码，欢迎关注，star，fork！ Min's blog 欢迎访问我的博客主页！ (Welcome to my blog website !)https://liweimin1996.github.io/

Plain python implementations of basic machine learning algorithms

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

Code, exercises and tutorials of my personal blog ! 📝

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

Implements common data science methods and machine learning algorithms from scratch in python. Intuition and theory behind the algorithms is also discussed.

This repository stores the files used for my summer internship's work on "teacher-student learning", an experimental method for training deep neural networks using a trained teacher model.

Learn advanced data science on real-life, curated problems

Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.

Code of my MOOC Course <Play with Machine Learning Algorithms>. Updated contents and practices are also included. 我在慕课网上的课程《Python3 入门机器学习》示例代码。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。

AI & Deep Learning Enthusiasts Meetup Project & Study Sessions

Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

Google Research

Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

A Deep Learning based project for creating line art portraits.

Multiple implementations for abstractive text summurization , using google colab

Reimplementation of DRAW

Implementations of the algorithms described in Differentiable plasticity: training plastic networks with gradient descent, a research paper from Uber AI Labs.

Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.

A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

Food Classification with Deep Learning in Keras / Tensorflow

A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks

An introductory series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.

Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai

Introduction to Data Science

Remove watermark automatically(Just can use for fixed position watermark till now). 自动水印消除算法的实现（目前只支持固定水印位置）。

Make a pull request. Let's hack the ocktober in an innovative way.

Lets Learn AI

Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning

Information about my experiences on ethical hacking 💀

I will update this repository to learn Machine learning with python with statistics content and materials

AIOpen是一个按人工智能三要素（数据、算法、算力）进行AI开源项目分类的汇集项目，项目致力于跟踪目前人工智能（AI）的深度学习（DL）开源项目，并尽可能地罗列目前的开源项目，同时加入了一些曾经研究过的代码。通过这些开源项目，使初次接触AI的人们对人工智能（深度学习）有更清晰和更全面的了解。

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Pytorch implementation of the DeepDream computer vision algorithm

R package to interface with OpenML

A repo with tutorials for algorithms from scratch

[Book-2019] Pragmatic AI: An Introduction to Cloud-based Machine Learning

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

Develop production ready deep learning code, deploy it and scale it

Generating multiple choice questions from text using Machine Learning.

Python implementation of some numerical (optimization) methods

This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms

Time Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms