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

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

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

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Cosine Annealing With Warmup

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Multi-resolution SeqMatch based long-term Place Recognition

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Code release for "BoxeR: Box-Attention for 2D and 3D Transformers"

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[ACM MM 2019 Oral] Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

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Hao Tang 67 Dec 14, 2022
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Clockwork Variational Autoencoder

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Learning to Initialize Neural Networks for Stable and Efficient Training

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Companion code for the paper "Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks" by Yatsura et al.

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A Japanese Medical Information Extraction Toolkit

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Implementation of QuickDraw - an online game developed by Google, combined with AirGesture - a simple gesture recognition application

QuickDraw - AirGesture Introduction Here is my python source code for QuickDraw - an online game developed by google, combined with AirGesture - a sim

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Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code

Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code.

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PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"

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Toolkit for collecting and applying prompts

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A high-performance distributed deep learning system targeting large-scale and automated distributed training.

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SelfAugment extends MoCo to include automatic unsupervised augmentation selection.

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