Dev tools · alternatives · 2026

24 alternatives to Open-source toolkit for ML model evaluation and active learning

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling. - encord-team/encord-active

This open-source toolkit helps developers evaluate machine learning models and implement active learning strategies. It provides tools for assessing model performance and selecting which data points to label for… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Open-source toolkit for ML model evaluation and active learning launched in 2023; newer entries below may have overtaken it.

1
Encord Active▲125
Search engine for your visual data
2023 · encord.com · its alternatives →
2
Igel – A CLI tool to run machine learning without writing code▲405
a delightful machine learning tool that allows you to train, test, and use models without writing code - nidhaloff/igel
2020 · github.com · its alternatives →
3
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 →
4
OpenBB ML/AI Toolkit▲80
A Financial machine learning toolkit that just works
2022 · openbb.co · its alternatives →
5
Label Studio 1.8.0 Release▲185
Open source data labelling platform for AI model tuning
2023 · labelstud.io · its alternatives →
6
Deepchecks Testing Package▲186
Open source tool for testing & validating your model & data
2022 · github.com · its alternatives →
7
Data Labeling Platform▲239
Manage your computer vision data labeling
2024 · labelyourdata.com · its alternatives →
8
An annotation tool for ML and NLP▲76
The easy way to turn text into structure data
2021 · getmarkup.com · its alternatives →
9
Every open source tool from the "What's HN working on" thread▲169
Public datsets made with https://getomni.ai/. Contribute to getomni-ai/datasets development by creating an account on GitHub.
2024 · github.com · its alternatives →
10
Cortex – machine learning infrastructure for developers▲86
Production infrastructure for machine learning at scale - cortexlabs/cortex
2019 · github.com · its alternatives →
11
Toolkit for LLM Fine-Tuning, Ablating and Testing▲14
Hello all! Very happy to share this toolkit that allows you to fine-tune your choice of open-source LLMs on your data! The toolkit also allows you to run ablation studies across LLMs, prompt designs, training configurations, and can ingest different data files -- all through just ONE YAML file! After fine-tuning, you can also run a bunch of tests to ensure that the fine-tuned LLM behaves as expected, enabling faster time-to-production! Why this toolkit? Why now? While closed-source LLMs have become popular for chat-based applications, enterprises are considering a shift to self-hosted SLMs…
2024 · github.com · its alternatives →
12
MonkeyLearn 3.0▲363
Get actionable data from text with machine learning
2018 · medallia.com · its alternatives →
13
ML Showcase▲214
A curated collection of machine learning projects
2017 · its alternatives →
14
Lightly▲148
Improve your machine learning models by using the right data
2021 · lightly.ai · its alternatives →
15
Microsoft Cognitive Toolkit▲110
Microsoft's deep learning toolkit
2017 · microsoft.com · its alternatives →
16
Labelf AI▲137
NLP Low code platform to train an AI with active learning
2021 · labelf.ai · its alternatives →
17
Openlayer – Test, fix, and improve your ML models▲53
Hey HN, my name is Vikas, and my cofounders Rish, Gabe and I are building Openlayer: http://openlayer.com/ Openlayer is an ML testing, evaluation, and observability platform designed to help teams pinpoint and resolve issues in their models. We were ML engineers experiencing the struggle that goes into properly evaluating models, making them robust to the myriad of unexpected edge cases they encounter in production, and understanding the reasons behind their mistakes. It was like playing an endless game of whack-a-mole with Jupyter notebooks and CSV files — fix one issue and…
2023 · openlayer.com · its alternatives →
18
ML Kit (by Google)▲195
Machine learning for mobile developers
2018 · developers.google.com · its alternatives →
19
TensorPort▲143
Help teams apply machine learning to real-world applications
2017 · its alternatives →
20
UpTrain – Open-source ML observability and refinement tool▲88
A couple of months ago, we left our jobs to build UpTrain AI, an open-source machine learning observability and refinement tool which helps users understand the performance of their models in production and improves them over time by identifying problematic data-points for retraining. Data drift, Distribution shifts, Model degradation, Edge cases - we have personally faced these problems in our previous organizations and have built a lot of tooling to solve them. We are building UpTrain so that others don’t need to build them and can solely focus on improving their ML models while we…
2023 · github.com · its alternatives →
21
Cortex – Open-source alternative to SageMaker for model serving▲65
Production infrastructure for machine learning at scale - GitHub - cortexlabs/cortex at v0.15.1
2020 · github.com · its alternatives →
22
Weights & Biases▲110
Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
23
Deploy ML Models on a Budget▲117
Deploy a ML inference service on a budget in less than 10 lines of code. - ebhy/budgetml
2021 · github.com · its alternatives →
24
Pi▲164
The ML & Data Science toolkit; built for Software Engineers.
2025 · 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 →