RoadMap and preparation material for Machine Learning and Data Science - From beginner to expert.

Related tags

Deep Learningdata-sciencemachine-learningdeep-learningpreparationinterview-preparationmachine-learning-projects
Overview

ML-and-DataScience-preparation

This repository has the goal to create a learning and preparation roadMap for Machine Learning Engineers and Data Scientists.

Project Structure

The repository is splittend into two macrofolders: Machine Learning and Data Science. Each section will have its own README file, containing a list of topic sorted from beginner to senior levels, with related e-learning resources or articles associated. Also in the README.md file, you will be able to find a Suggested Books section, containing a list of books useful for theory preparation, practice or interview preparation.

Collaborate to the Project

Any feedback or collaboration is more than welcome.

How to collaborate

  • Star the repository
  • Clone the repository
  • Add your changes
  • Create a Pull Request

Host

Special thanks to LeadTheFuture for welcoming and supporting this initiative.

Contributors

Owner
GitHub Repository https://leadthefuture.tech/
Automated image registration. Registrationimation was too much of a mouthful.

alignimation Automated image registration. Registrationimation was too much of a mouthful. This repo contains the code used for my blog post Alignimat

Ethan Rosenthal 9 Oct 13, 2022
Warning: This project does not have any current developer. See bellow.

Pylearn2: A machine learning research library Warning : This project does not have any current developer. We will continue to review pull requests and

Laboratoire d’Informatique des Systèmes Adaptatifs 2.7k Dec 26, 2022
Combinatorial model of ligand-receptor binding

Combinatorial model of ligand-receptor binding The binding of ligands to receptors is the starting point for many import signal pathways within a cell

Mobolaji Williams 0 Jan 09, 2022
Code for "3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop"

PyMAF This repository contains the code for the following paper: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop Hongwe

Hongwen Zhang 450 Dec 28, 2022
LibFewShot: A Comprehensive Library for Few-shot Learning.

LibFewShot Make few-shot learning easy. Supported Methods Meta MAML(ICML'17) ANIL(ICLR'20) R2D2(ICLR'19) Versa(NeurIPS'18) LEO(ICLR'19) MTL(CVPR'19) M

<a href=[email protected]&L"> 603 Jan 05, 2023
An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.

An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise

45 Dec 08, 2022
VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

What's New Below we share, in reverse chronological order, the updates and new releases in VISSL. All VISSL releases are available here. [Oct 2021]: V

Meta Research 2.9k Jan 07, 2023
masscan + nmap + Finger

说明 个人根据使用习惯修改masnmap而来的一个小工具。调用masscan做全端口扫描，再调用nmap做服务识别，最后调用Finger做Web指纹识别。工具使用场景适合风险探测排查、众测等。 使用方法 安装依赖 pip3 install -r requirements.txt -i https:/

Ryan 3 Mar 25, 2022
A New Open-Source Off-road Environment for Benchmark Generalization of Autonomous Driving

A New Open-Source Off-road Environment for Benchmark Generalization of Autonomous Driving Isaac Han, Dong-Hyeok Park, and Kyung-Joong Kim IEEE Access

13 Dec 27, 2022
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

Learning to Classify Images without Labels This repo contains the Pytorch implementation of our paper: SCAN: Learning to Classify Images without Label

Wouter Van Gansbeke 1.1k Dec 30, 2022
RTSeg: Real-time Semantic Segmentation Comparative Study

Real-time Semantic Segmentation Comparative Study The repository contains the official TensorFlow code used in our papers: RTSEG: REAL-TIME SEMANTIC S

Mennatullah Siam 592 Nov 18, 2022
arxiv-sanity, but very lite, simply providing the core value proposition of the ability to tag arxiv papers of interest and have the program recommend similar papers.

arxiv-sanity, but very lite, simply providing the core value proposition of the ability to tag arxiv papers of interest and have the program recommend similar papers.

Andrej 671 Dec 31, 2022
A library that allows for inference on probabilistic models

Bean Machine Overview Bean Machine is a probabilistic programming language for inference over statistical models written in the Python language using

Meta Research 234 Dec 29, 2022
Implementation of Deep Deterministic Policy Gradiet Algorithm in Tensorflow

ddpg-aigym Deep Deterministic Policy Gradient Implementation of Deep Deterministic Policy Gradiet Algorithm (Lillicrap et al.arXiv:1509.02971.) in Ten

Steven Spielberg P 247 Dec 07, 2022
PyTorch implementaton of our CVPR 2021 paper "Bridging the Visual Gap: Wide-Range Image Blending"

Bridging the Visual Gap: Wide-Range Image Blending PyTorch implementaton of our CVPR 2021 paper "Bridging the Visual Gap: Wide-Range Image Blending".

Chia-Ni Lu 69 Dec 20, 2022
Robust & Reliable Route Recommendation on Road Networks

NeuroMLR: Robust & Reliable Route Recommendation on Road Networks This repository is the official implementation of NeuroMLR: Robust & Reliable Route

4 Dec 20, 2022
Quantify the difference between two arbitrary curves in space

similaritymeasures Quantify the difference between two arbitrary curves Curves in this case are: discretized by inidviudal data points ordered from a

Charles Jekel 175 Jan 08, 2023
(AAAI2022) Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Semantic Segmentation

SM-PPM This is a Pytorch implementation of our paper "Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Seman

W-zx-Y 10 Dec 07, 2022
Offical implementation for "Trash or Treasure? An Interactive Dual-Stream Strategy for Single Image Reflection Separation".

Trash or Treasure? An Interactive Dual-Stream Strategy for Single Image Reflection Separation (NeurIPS 2021) by Qiming Hu, Xiaojie Guo. Dependencies P

Qiming Hu 31 Dec 20, 2022
Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase

Ranger-Deep-Learning-Optimizer Ranger - a synergistic optimizer combining RAdam (Rectified Adam) and LookAhead, and now GC (gradient centralization) i

Less Wright 1.1k Dec 21, 2022