Alternatives and similar repositories for fsdl-text-recognizer-project

Users that are interested in fsdl-text-recognizer-project are comparing it to the libraries listed below

• the-full-stack / course-gitbook
  Full Stack Deep Learning Online Course
  ☆898Updated 3 years ago
• Machine-Learning-Tokyo / DL-workshop-series
  Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)
  ☆937Updated last year
• GoogleCloudPlatform / keras-idiomatic-programmer
  Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras M…
  ☆818Updated 4 years ago
• mrdbourke / cs329s-ml-deployment-tutorial
  Code and files to go along with CS329s machine learning model deployment tutorial.
  ☆607Updated 2 years ago
• Machine-Learning-Tokyo / papers-with-annotations
  Research papers with annotations, illustrations and explanations
  ☆829Updated 4 years ago
• dair-ai / pytorch_notebooks
  🔥 A collection of PyTorch notebooks for learning and practicing deep learning
  ☆572Updated 2 years ago
• the-full-stack / fsdl-text-recognizer-2021-labs
  Complete deep learning project developed in Full Stack Deep Learning, Spring 2021
  ☆448Updated 3 years ago
• sayakpaul / TF-2.0-Hacks
  Contains my explorations of TensorFlow 2.x
  ☆382Updated 3 years ago
• Machine-Learning-Tokyo / Math_resources
  ☆344Updated 4 years ago
• dair-ai / nlp_paper_summaries
  ✍️ A carefully curated list of NLP paper summaries
  ☆1,480Updated 3 years ago
• anhquan0412 / basic_model_scratch
  Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library
  ☆595Updated 5 years ago
• muellerzr / Practical-Deep-Learning-for-Coders-2.0
  Notebooks for the "A walk with fastai2" Study Group and Lecture Series
  ☆748Updated 3 years ago
• fastai / course-v4
  Please use fastbook's /clean folder instead of this
  ☆447Updated 4 years ago
• fastai / fastai_dev
  fast.ai early development experiments
  ☆645Updated 2 years ago
• hundredblocks / ml-powered-applications
  Companion repository for the book Building Machine Learning Powered Applications
  ☆679Updated 2 years ago
• chiphuyen / just-pandas-things
  An ongoing list of pandas quirks
  ☆971Updated 2 years ago
• visual-ml-notes / visual-machine-learning-notes
  Machine Learning Conference & Summer School Notes. 🦄
  ☆574Updated 4 years ago
• sotte / pytorch_tutorial
  PyTorch Tutorial (1.7)
  ☆457Updated 4 years ago
• fastai / fastai2
  Temporary home for fastai v2 while it's being developed
  ☆646Updated 4 years ago
• dair-ai / d2l-study-group
  🧠 Material for the Deep Learning Study Group
  ☆394Updated 3 years ago
• rasbt / stat453-deep-learning-ss20
  STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)
  ☆572Updated 5 years ago
• hiromis / notes
  ☆1,041Updated 4 years ago
• Building-ML-Pipelines / building-machine-learning-pipelines
  Code repository for the O'Reilly publication "Building Machine Learning Pipelines" by Hannes Hapke & Catherine Nelson
  ☆596Updated 2 years ago
• dair-ai / nlp_fundamentals
  📘 Contains a series of hands-on notebooks for learning the fundamentals of NLP
  ☆371Updated 4 years ago
• vahidk / EffectivePyTorch
  PyTorch tutorials and best practices.
  ☆1,689Updated 3 months ago
• wandb / awesome-dl-projects
  This is a collection of the code that accompanies the reports in The Gallery by Weights & Biases.
  ☆340Updated 3 years ago
• The-AI-Summer / Deep-Learning-In-Production
  Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
  ☆1,169Updated 2 years ago
• alirezadir / Production-Level-Deep-Learning
  A guideline for building practical production-level deep learning systems to be deployed in real world applications.
  ☆4,484Updated last month
• rasbt / stat479-deep-learning-ss19
  Course material for STAT 479: Deep Learning (SS 2019) at University Wisconsin-Madison
  ☆535Updated 6 years ago
• the-black-knight-01 / Data-Science-Competitions
  Goal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).
  ☆805Updated 5 years ago