803 Open source projects that are alternatives of or similar to Ml Roadmap

This repository contains notes and projects of Data scientist track from dataquest course work.

The Cutest Deep Learning Framework which is also a wonderful Declarative Language

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A curated list of applied machine learning and data science notebooks and libraries across different industries.

Season 2 of @twosigma's artificial intelligence programming challenge

【不定期更新】收集整理的一些网站中（如知乎、Quora、Reddit、Stack Exchange等）与深度学习、机器学习、强化学习、数据科学相关的有价值的问题

This repositary is a combination of different resources lying scattered all over the internet. The reason for making such an repositary is to combine all the valuable resources in a sequential manner, so that it helps every beginners who are in a search of free and structured learning resource for Data Science. For Constant Updates Follow me in …

Deeplearning Algorithms Tutorial

Implementation of cs229(Machine Learning taught by Andrew Ng) in python.

In this repo I will try to gather all of the projects related to data science with clean datasets and high accuracy models to solve real world problems.

Different types of data analytics projects : EDA, PDA, DDA, TSA and much more.....

Real-time portrait segmentation for mobile devices

No dependency caffe replacement

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

A collection of some datasets for segmentation / saliency detection. Welcome to PR...😄

A curated list of amazingly awesome Cybersecurity datasets

This is the public roadmap for AWS container services (ECS, ECR, Fargate, and EKS).

SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing

Action recognition using soft attention based deep recurrent neural networks

List of Deep Learning Cloud Providers

A set of tools to use in Microsoft Azure Form Recognizer and OCR services.

SqueezeNet implementation with Keras Framework

The Front-End Developer Learning Roadmap by Frontend Masters

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

Implementing machine learning algorithms from scratch.

Plain python implementations of basic machine learning algorithms

Multiple implementations for abstractive text summurization , using google colab

Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

Minimal and clean examples of machine learning algorithms implemented in Julia

[High Performance / MAX 30 FPS] RaspberryPi3(RaspberryPi/Raspbian Stretch) or Ubuntu + Multi Neural Compute Stick(NCS/NCS2) + RealSense D435(or USB Camera or PiCamera) + MobileNet-SSD(MobileNetSSD) + Background Multi-transparent(Simple multi-class segmentation) + FaceDetection + MultiGraph + MultiProcessing + MultiClustering

High-level Deep Learning Framework written in Kotlin and inspired by Keras

Vector Hub - Library for easy discovery, and consumption of State-of-the-art models to turn data into vectors. (text2vec, image2vec, video2vec, graph2vec, bert, inception, etc)

A curated list of Monte Carlo tree search papers with implementations.

Developing Options Trading Strategies using Technical Indicators and Quantitative Methods

Deep Learning Projects that Build Themselves

YOLO for object detection tasks

增值税发票OCR识别，使用flask微服务架构，识别type：增值税电子普通发票，增值税普通发票，增值税专用发票；识别字段为：发票代码、发票号码、开票日期、校验码、税后金额等

DilatedNet in Keras for image segmentation

The best resources around Machine Learning

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

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

PyTorch1.x tutorials, examples and some books I found 【不定期更新】整理的PyTorch 1.x 最新版教程、例子和书籍

book

Tensorflow implementation of Restricted Boltzmann Machine

CosmiQ Works Geospatial Machine Learning Analysis Toolkit

Python learning to rank (LTR) toolkit

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

Deep learning framework realized by Numpy purely, supports for both Dynamic Graph and Static Graph with GPU acceleration

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Mathematica implementations of machine learning algorithms used for prediction and personalization.

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cuDF - GPU DataFrame Library

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语音识别理论，论文和PPT

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Roadmap to becoming a Visual-SLAM developer in 2021

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🎢 Roadmap para se tornar um desenvolvedor web! Atualização 2021!