Life & fun · alternatives · 2026

24 alternatives to Encrypted Deep Learning Classification with PyTorch and PySyft

Update as of November 18, 2021: The version of PySyft mentioned in this post has been deprecated. Any implementations using this older version of PySyft are…

This is a deprecated blog post demonstrating encrypted deep learning classification using PyTorch and PySyft. It shows how to build a private neural network that classifies MNIST images through Secure Multi-Party… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Encrypted Deep Learning Classification with PyTorch and PySyft launched in 2019; newer entries below may have overtaken it.

1
Encrypted Deep Learning in PyTorch▲37
Perform data science on data that remains in someone else's server - OpenMined/PySyft
2018 · github.com · its alternatives →
2
TensorFlow 1.0▲823
Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
3
Train a Convolutional Neural Nets Using Multi-Party Computation▲28
Most efforts to privately train machine-learning models either use homomorphic encryption or secure multi-party computation (MPC). Recent insights indicate…
2018 · blog.openmined.org · its alternatives →
4
Thinc, a new deep learning library by the makers of spaCy and FastAPI▲250
Thinc is a lightweight type-checked deep learning library for composing models, with support for layers defined in frameworks like PyTorch and TensorFlow.
2020 · thinc.ai · its alternatives →
5
TensorFlow 1.0▲80
Open-source machine learning library by Google
2018 · tensorflow.org · its alternatives →
6
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 →
7
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 →
8
Natural Language Processing Demystified (Part One)▲166
Hi HN: I published part one of my free NLP course. The course is intended to help anyone who knows Python and a bit of math go from the very basics all the way to today's mainstream models and frameworks. I strive to balance theory and practice and so every module consists of detailed explanations and slides along with a Colab notebook (in most modules) putting the theory into practice. In part one, we cover text preprocessing, how to turn text into numbers, and multiple ways to classify and search text using "classical" approaches. And along the way, we'll pick up useful bits on how to use…
2022 · nlpdemystified.org · its alternatives →
9
Weights & Biases▲110
Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
10
I built a tensor library from scratch in C++/CUDA▲119
Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…
2025 · github.com · its alternatives →
11
Autograd.c – A tiny ML framework built from scratch▲85
built a tiny pytorch clone in c after going through prof. vijay janapa reddi's mlsys book: mlsysbook.ai/tinytorch/ perfect for learning how ml frameworks work under the hood :)
Dec 2025 · github.com · its alternatives →
12
Faster R-CNN object detector implemented in PyTorch and TensorFlow 2▲15
Fresh and (I think) clean implementations of Faster R-CNN in PyTorch and TensorFlow 2/Keras. I wanted to learn about object detectors and decided to understand and implement a foundational model in the field, Faster R-CNN (elements of which are still used in modern models to this day), using the paper alone. That proved to be more difficult than expected and I had to relent and take a peak at existing implementations to fill in some important gaps. I've documented my struggles and learnings in the README for others to benefit from. I also wanted to solidify my understanding of…
2022 · github.com · its alternatives →
13
PyBV – A Python Implementation of the BV Homomorphic Encryption Scheme▲9
DEPRECATED- see https://github.com/OpenMined/OpenMined or https://github.com/OpenMined/PySyft - iamtrask/PyBV
2017 · github.com · its alternatives →
14
Neural Network Evolution Playground with Backprop NEAT▲73
2016 · blog.otoro.net · its alternatives →
15
Cant – Library written in Rust that provides PyTorch-like functionality▲50
Hey! This is something i have been working on. A tiny neural networking lib to learn how something like pytorch works, and to improve my own coding standards.
2025 · github.com · its alternatives →
16
I built a deep learning engine from scratch in Python▲30
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 →
17
A completely handwritten deep neural network in python▲13
A handwritten multilayer perceptron classifer using numpy. - meetvora/mlp-classifier
2016 · github.com · its alternatives →
18
Peer-To-Peer Federated Deep Learning Using IPFS and PyTorch▲15
2018 · youtube.com · its alternatives →
19
Logistic Regression Training on Encrypted Data with FHE▲8
Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on top of Concrete, with bindings to traditional ML frameworks. - concrete-ml/docs/advanced_examples/LogisticRegressionTraining.ipynb at release/1.4.x · zama-ai/concrete-ml
2024 · github.com · its alternatives →
20
A Haskell DSL for deep learning models▲10
A DSL for deep neural networks, supporting Caffe and Torch - ajtulloch/dnngraph
2015 · github.com · its alternatives →
21PL
Python library to scan ML models for vulnerabilities▲20
Hi! I’ve been working on this automatic scanner for ML models to detect issues like underperforming data slices, overconfidence in predictions, robustness problems, and others. It supports all main Python ML frameworks (sklearn, torch, xgboost, …) and integrates with the quality assurance solution we are building at Giskard AI (https://giskard.ai) to systematically test models before putting them in production. It is still a beta and I would love to hear your feedback if you have the time to try it out. We have quite a few tutorials in the docs with ready-made colab notebooks to…
2023 · docs.giskard.ai · its alternatives →
22
Tensor Spy: inspect NumPy and PyTorch tensors in the browser, no upload▲22
We needed a side project to give agentic coding a try, and created tensorspy.com together with Junie and ChatGPT 5.2. Tensor Spy lets you quickly inspect the contents of numpy & pytorch tensors locally (your tensors are not uploaded to any servers). This is useful to validate your deep learning data pipelines, to check which layers in your diverging model are actually going haywire, and just because it's kind of cool & a lot more convenient for one-off inspections than loading things up in python. If you work with diffusion models, inspecting the latent space can be quite informative: you…
Mar 2026 · tensorspy.com · its alternatives →
23
Open-Sourcing Google's Lattice Models in PyTorch▲13
We're a group of engineers, AI/ML enthusiasts, and author of this paper https://openreview.net/forum?id=0pxiMpCyBtr who saw a closed door in AI/ML and decided to open it. This project is a PyTorch reimagining of Google's TensorFlow Lattice models, which despite being labeled open-source, were previously open in name only (you have to be a Googler to contribute). Also, side point…TensorFlow is dying https://thenextweb.com/news/why-tensorflow-for-python-is-dyi... Here's the deal: Lattice models excel in making AI interpretable—key for sectors where…
2023 · github.com · its alternatives →
24
Generating Collisions on NeuralHash▲22
Proof of Concept : generating collisions on a neural perceptual hash - collisionLSH.py
2021 · gist.github.com · its alternatives →

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