Dev tools · alternatives · 2026
24 alternatives to Deep Learning for Program Synthesis
By Rishabh Singh, Jacob Devlin, Abdelrahman Mohamed, and Pushmeet Kohli, Microsoft Research Despite the many advances in computing over the past decades, the actual process of writing computer software has not fundamentally changed — a programmer must manually code the exact algorithmic logic of a p
Deep Learning for Program Synthesis is a research project from Microsoft that uses deep neural networks to automatically generate computer code. Rather than requiring programmers to manually write algorithmic logic… 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 for Program Synthesis launched in 2017; newer entries below may have overtaken it.
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2019 · zecoda.com · its alternatives →
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https://the-pocket.github.io/Tutorial-Codebase-Knowledge/
2025 · github.com · its alternatives →
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Neural network inference the Unix way. Contribute to cloudkj/layer development by creating an account on GitHub.
2019 · github.com · its alternatives →
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Maxium AI (Beta)▲302Optimise developer efficiency, going beyond lines of code
2024 · maxium.ai · its alternatives →
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I’ve spent the last few months building a deep learning engine completely from scratch in Python (using only math and random). What started as a basic linear algebra calculator project grew into a symbolic tensor system with autodiff, custom matrix ops, attention mechanisms, LayerNorm, GELU, and even a text generation demo trained on the Brown corpus. I'm still an undergrad, so my main goal is to deeply understand how deep learning actually works under the hood - gradients, attention, backpropagation, optimizers - by building it step-by-step with full visibility into everything, and without…
2025 · github.com · its alternatives →
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Want to create a Deep Learning framework from scratch? Checkout this resource: https://koki0702.github.io/dezero-book/en/index.html In this book, you will create a deep learning framework called "DeZero" from scratch (from zero), which is the original framework of this book. With minimal code, the framework's modern features are realized. In this book, you will make this small - yet powerful enough - framework in a total of 60 steps. It will deepen your knowledge of modern frameworks such as PyTorch and TensorFlow.
2022 · koki0702.github.io · its alternatives →
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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 →
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Skillkit▲252It's an open-source project that lets you create, translate, and work with multiple agents at the same time, and more.
Feb 2026 · agenstskills.com · its alternatives →
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- 11DL
2019 · beta.aifiddle.io · its alternatives →
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Software for DL application development without coding.
2018 · ai-dlp.com · its alternatives →
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2016 · danielheres.space · its alternatives →
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Sonnet▲134A new library for constructing neural networks from DeepMind
2017 · deepmind.google · its alternatives →
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DeepWiki provides up-to-date documentation you can talk to, for every repo in the world. Think Deep Research for GitHub - powered by Devin.
2025 · deepwiki.com · its alternatives →
- 17N5
2020 · nn-512.com · its alternatives →
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Trying to do gradient descent using automatic differentiation over branchy programs? Or to combine them with neural networks for end-to-end training? Then this might be interesting to you. We develped DiscoGrad, a tool for automatic differentiation through C++ programs involving input-dependent control flow (e.g., "if (f(x) < c) { ... }", differentiating wrt. x) and randomness. Our initial motivation was to enable the use of gradient descent with simulations, which often rely heavily on such discrete branching. The latter makes plain autodiff mostly useless, since it can only account for the…
2024 · github.com · its alternatives →
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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 →
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Weights & Biases▲110Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
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Train and deploy speech AI models for free
2020 · console.deepgram.com · its alternatives →
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A minimalist deep learning library written from scratch in Python - sradc/SmallPebble
2021 · github.com · its alternatives →
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: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 →
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APG9 hadir sebagai zona gaming terbaik dengan peluang menang besar dan bonus dahsyat di setiap putaran. Rasakan sensasi cuan sekarang juga!.
2017 · deepforge.org · its alternatives →
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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 →