Work · alternatives · 2026

24 alternatives to Collection of deep learning implementations with side-by-side notes

This is a collection of deep learning implementations organized with parallel explanatory notes. It provides side-by-side code and documentation to help users understand how neural networks work. The resource is… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Collection of deep learning implementations with side-by-side notes launched in 2021; newer entries below may have overtaken it.

1
Annotated neural network implementations▲7
Implementations of neural networks with side-by-side notes
2020 · its alternatives →
2
Simple and comprehensive tutorials in Deep Learning using TensorFlow▲157
Simple and comprehensive tutorials in TensorFlow. Contribute to easy-tensorflow/easy-tensorflow development by creating an account on GitHub.
2018 · github.com · its alternatives →
3
Comprehensive Tutorials in Deep Learning Using TensorFlow▲327
:satellite: Simple and ready-to-use tutorials for TensorFlow - GitHub - instillai/TensorFlow-Course: :satellite: Simple and ready-to-use tutorials for TensorFlow
2018 · github.com · its alternatives →
4
TensorFlow 1.0▲823
Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
5
Deep Learning in TensorFlow – The Roadmap for Study and Learning▲146
:satellite: Organized & Useful Resources about Deep Learning with TensorFlow - astorfi/TensorFlow-World-Resources
2019 · github.com · its alternatives →
6
TensorFlow-Resources – Organized and Useful Resources about TensorFlow▲152
:satellite: Organized & Useful Resources about Deep Learning with TensorFlow - astorfi/TensorFlow-World-Resources
2018 · github.com · its alternatives →
7
Deep Learning▲67
The textbook for modern machine learning
2016 · amazon.com · its alternatives →
8
Neural Networks and Deep Learning▲95
Core concepts behind neural networks and deep learning
2015 · neuralnetworksanddeeplearning.com · its alternatives →
9IC
I co-wrote a book on training Deep Learning models in Go▲45
A friend and I wrote a book on how to build and train Deep Learning models in Go. We wanted it to be a useful reference for deep learning basics for Go programmers. Deep Learning is slowly seeping into everything we use every day and we thought it would be great if more people could do it in Go. The book is available here and on Amazon as well. https://www.packtpub.com/big-data-and-business-intelligence/hands-deep-learning-go We would appreciate any feedback and we're always looking to improve.
2019 · its alternatives →
10
Fast Deep Reinforcement Learning Course▲148
I worked on this applied Deep Reinforcement Learning course for the better part of 2021. I made a Datacamp course [0] before, and this served as my inspiration to make an applied Deep RL series. Normally, Deep RL courses teach a lot of mathematically involved theory. You get the practical applications near the end (if at all). I have tried to turn that on its head. In the top-down approach, you learn practical skills first, then go deeper later. This is much more fun. This course (the first in a planned multi-part series) shows how to use the Deep Reinforcement Learning framework RLlib to…
2022 · courses.dibya.online · its alternatives →
11DL
Deep Learning GUI to Create, Train and Visualize Models in a Browser▲216
2019 · beta.aifiddle.io · its alternatives →
12
Simple Deep Learning Tutorials using Microsoft Cognitive Toolkit▲126
:earth_americas: Simple and ready-to-use deep learning examples for the Microsoft Cognitive Toolkit (CNTK) - CNTK-World/README.rst at master · astorfi/CNTK-World
2017 · github.com · its alternatives →
13
Weights & Biases▲110
Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
14
Neural networks tutorial series with code▲107
The simplest form of an artificial neural network explained and demonstrated. - GitHub - gokadin/ai-simplest-network: The simplest form of an artificial neural network explained and demonstrated.
2020 · github.com · its alternatives →
15
Set of trained deep learning models for computer vision▲127
Keras code and weights files for popular deep learning models. - fchollet/deep-learning-models
2016 · github.com · its alternatives →
16
Sonnet▲134
A new library for constructing neural networks from DeepMind
2017 · deepmind.google · its alternatives →
17AV
A Visual and Interactive Guide to the Basics of Neural Networks▲63
Discussions: Hacker News (63 points, 8 comments), Reddit r/programming (312 points, 37 comments) Translations: Arabic, French, Spanish Update: Part 2 is now live: A Visual And Interactive Look at Basic Neural Network Math Motivation I’m not a machine learning expert. I’m a software engineer by train
2016 · jalammar.github.io · its alternatives →
18
O’Reilly Fundamentals of Deep Learning▲143
Designing next-generation Artificial intelligence algorithms
2016 · oreilly.com · its alternatives →
19
TensorFlow 1.0▲80
Open-source machine learning library by Google
2018 · tensorflow.org · its alternatives →
20
Diffgram▲104
Learn to work with deep learning without code
2019 · github.com · its alternatives →
21GC
Graph Convolutional Networks – Intro to neural networks on graphs▲106
Many important real-world datasets come in the form of graphs or networks: social networks, knowledge graphs, protein-interaction networks, the World Wide Web, etc. (just to name a few). Yet, until recently, very little attention has been devoted to the generalization of neural...
2016 · tkipf.github.io · its alternatives →
22
I wrote a minimal deep learning library from scratch in Python▲25
A minimalist deep learning library written from scratch in Python - sradc/SmallPebble
2021 · github.com · its alternatives →
23
A perceptron with stochastic gradient descent in Go▲94
A single / multi layer / recurrent neural network written in Golang. - made2591/go-perceptron-go
2017 · github.com · its alternatives →
24
Deep Learning Gallery▲87
A curated list of awesome deep learning projects
2017 · deeplearninggallery.com · its alternatives →

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