Alternatives and similar repositories for indaba-pracs-2019

Users that are interested in indaba-pracs-2019 are comparing it to the libraries listed below

• khipu-ai / practicals-2019
  Practical notebooks for Khipu 2019, held in Universidad de la República in Montevideo.
  ☆244Updated 5 years ago
• Machine-Learning-Tokyo / MLT_Talks
  Slides, videos and other resources from MLT Talks
  ☆109Updated 4 years ago
• eemlcommunity / PracticalSessions2020
  Repository for tutorial sessions at EEML2020
  ☆272Updated 4 years ago
• DanielhCarranza / ml-production-template
  This codebase is a starting point to get your Machine Learning project into Production.
  ☆43Updated 4 years ago
• nassma2019 / PracticalSessions
  NASSMA summer school practicals
  ☆18Updated 5 years ago
• Machine-Learning-Tokyo / MLT_starterkit
  ☆92Updated 4 years ago
• the-full-stack / fsdl-text-recognizer
  Repo that generates https://github.com/full-stack-deep-learning/fsdl-text-recognizer-project
  ☆58Updated 2 years ago
• DebPanigrahi / Machine-Learning
  Machine learning algorithms
  ☆112Updated 6 years ago
• Machine-Learning-Tokyo / AI-ML-Newsletter
  AI Digest: Monthly updates on AI and ML topics
  ☆105Updated 4 years ago
• shreyashankar / toy-ml-pipeline
  Toy example of an applied ML pipeline for me to experiment with MLOps tools.
  ☆209Updated 3 years ago
• lavanyashukla / neural_networks
  ☆50Updated 4 years ago
• jessicayung / machine-learning-flashcards
  Machine learning flashcards
  ☆221Updated 3 years ago
• Machine-Learning-Tokyo / Deep_Reinforcement_Learning
  Resources, papers, tutorials
  ☆125Updated 5 years ago
• Machine-Learning-Tokyo / Math_resources
  ☆343Updated 4 years ago
• Machine-Learning-Tokyo / Intro-to-GANs
  This code was developed for the Intro to GANs workshop for Machine Learning Tokyo (MLT).
  ☆66Updated 6 years ago
• Machine-Learning-Tokyo / practical-ml-implementations
  ML implementations for practical use
  ☆15Updated 5 years ago
• brohrer / cottonwood
  A flexible neural network framework for running experiments and trying ideas.
  ☆81Updated 5 years ago
• deep-learning-indaba / indaba-2018
  Practical Notebooks for the Deep Learning Indaba 2018
  ☆145Updated 6 years ago
• AdrienLE / dl_book_notes
  ☆60Updated 7 years ago
• alessiamarcolini / deep-learning_best-practices
  ☆107Updated 6 years ago
• JohnGiorgi / mathematics-for-machine-learning
  A set of notes, in the form of a simple Github Pages site, which will serve as a complete crash course on the various areas of mathematic…
  ☆64Updated 5 years ago
• benjamin-du / fastpractice
  Exercises for FastAI v2
  ☆19Updated 4 years ago
• abhishekkrthakur / e01
  ☆38Updated 5 years ago
• Machine-Learning-Tokyo / __init__
  ☆138Updated 2 years ago
• ADGEfficiency / teaching-monolith
  Data science teaching materials
  ☆149Updated 3 months ago
• vopani / fortyone
  Machine Learning begins with Human Learning
  ☆108Updated 3 years ago
• fg91 / Neural-Image-Caption-Generation-Tutorial
  ☆66Updated 5 years ago
• amueller / aml
  Applied Machine Learning with Python
  ☆79Updated last year
• jmugan / modern_practical_nlp
  This course covers how you can use NLP to do stuff.
  ☆267Updated 4 years ago
• Machine-Learning-Tokyo / generative_deep_learning
  Generative Deep Learning Sessions led by Anugraha Sinha (Machine Learning Tokyo)
  ☆24Updated 5 years ago