Dev tools · alternatives · 2026
24 alternatives to OverBoard, Like TensorBoard but with Native Python GUI, for PyTorch
Pure Python dashboard for monitoring deep learning experiments (like TensorBoard for PyTorch/JAX/etc, without a browser) - jotaf98/overboard
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. OverBoard, Like TensorBoard but with Native Python GUI, for PyTorch launched in 2019; newer entries below may have overtaken it.
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:speech_balloon: Machine Learning Course with Python: - GitHub - instillai/machine-learning-course: :speech_balloon: Machine Learning Course with Python:
2019 · github.com · its alternatives →
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: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 →
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AI Infra / AI Orchestration / AI Control Plane. Contribute to polyaxon/polyaxon development by creating an account on GitHub.
2017 · github.com · its alternatives →
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TensorZero▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
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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 →
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Weights & Biases▲110Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
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Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood. - xmartlabs/Bender
2017 · github.com · its alternatives →
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An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack
2016 · github.com · its alternatives →
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Simple and comprehensive tutorials in TensorFlow. Contribute to easy-tensorflow/easy-tensorflow development by creating an account on GitHub.
2018 · github.com · its alternatives →
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I'm a machine learning engineer and researcher. I got fed up with how difficult it is to understand why neural networks behave the way they do, so i wrote a library to help with it. Comgra (computation graph analysis) is a library you can use with pytorch to extract all the tensor data you care about and visualize it graphically in a browser. This allows for a much more detailed analysis of what is happening than the usual approach of using tensorboard. You can go investigate tensors as training proceeds, drill down into individual neurons, inspect single data sets that are of special…
2023 · github.com · its alternatives →
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Datature Portal▲100No-code webapp to visualize your deep neural nets
2021 · datature.io · its alternatives →
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A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python. - reiinakano/xcessiv
2017 · github.com · its alternatives →
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Vibe profile your ML models to get max performance.
2025 · github.com · its alternatives →
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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 →
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I started writing this mostly for the Pi but ended up building it to support multiple Linux OSs. It's intended to be just that, a small dashboard providing real-time details on the usage. Still a work in progress and was done for fun, there's a demo as well :). MIT license. https://pydash.net or http://k3oni.github.io/pydash
2014 · its alternatives →
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:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling - GitHub - achillesrasquinha/bulbea: :boar: Deep Learning based Python Library for Stock Market Prediction and Modelling
2017 · github.com · 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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A minimalist deep learning library written from scratch in Python - sradc/SmallPebble
2021 · github.com · its alternatives →
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Interactive Computing for Humans. Contribute to herqooly/herqooly development by creating an account on GitHub.
2020 · github.com · its alternatives →
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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 →
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