AI · alternatives · 2026

This is an online course on deep learning and neural networks offered through AWS, available on the Teachable platform. It is designed for learners interested in studying artificial intelligence and machine learning… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Deep Learning and Neural Networks Course on AWS launched in 2017; newer entries below may have overtaken it.

1. 1
   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 →

2. 2
   AWS DeepLens▲168

   Deep learning enabled video camera for developers

   2017 · aws.amazon.com · its alternatives →

3. 3
   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 →

4. 4
   I trained a deep learning model to build sites for me▲397

   2019 · zecoda.com · its alternatives →

5. 5
   I built a game to help you learn neural network architectures▲321

   2024 · graphgame.sabrina.dev · its alternatives →

6. 6
   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 →

7. 7
   A Course on Deep Learning Using Google's TensorFlow▲39

   :earth_americas: Simple and ready-to-use tutorials for TensorFlow - astorfi/TensorFlow-World

   2019 · github.com · its alternatives →

8. 8
   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 →

9. 9
   Amazon Rekognition▲318

   Deep learning-based image recognition API from Amazon

   2016 · aws.amazon.com · its alternatives →

10. 10
    O’Reilly Fundamentals of Deep Learning▲143

    Designing next-generation Artificial intelligence algorithms

    2016 · oreilly.com · its alternatives →

11. 11
    Neural Networks and Deep Learning▲95

    Core concepts behind neural networks and deep learning

    2015 · neuralnetworksanddeeplearning.com · its alternatives →

12. 12
    AWS DeepRacer▲119

    A 1/18th scale race car to learn machine learning 🚗

    2018 · aws.amazon.com · its alternatives →

13. 13
    Applying the Unix philosophy to neural networks▲251

    Neural network inference the Unix way. Contribute to cloudkj/layer development by creating an account on GitHub.

    2019 · github.com · its alternatives →

14. 14
    Collection of deep learning implementations with side-by-side notes▲251

    2021 · nn.labml.ai · its alternatives →

15. 15GC
    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 →

16. 16DL
    Deep Learning GUI to Create, Train and Visualize Models in a Browser▲216

    2019 · beta.aifiddle.io · its alternatives →

17. 17
    Deep Learning▲67

    The textbook for modern machine learning

    2016 · amazon.com · its alternatives →

18. 18
    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 →

19. 19
    Amazon Machine Learning ▲211

    Machine learning made easy for developers of any skill level

    2015 · aws.amazon.com · its alternatives →

20. 20
    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 →

21. 21
    LambdaNet – A functional neural network library written in Haskell▲56

    Purely functional artificial neural network library implemented in Haskell. - jbarrow/LambdaNet

    2014 · github.com · its alternatives →

22. 22IM
    I made a 5 hour neural networks class with no prerequisites▲17

    2017 · neuralnetsforhackers.teachable.com · its alternatives →

23. 23
    AETROS▲155

    Create, train and monitor deep neural networks

    2016 · its alternatives →

24. 24
    AWS Fundamentals▲152

    AWS for the real world, not for certifications

    2023 · awsfundamentals.com · its alternatives →

Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →