Jupyter notebooks implement and derive machine learning algorithms from first principles using NumPy.
The Best Hands-on Train and Deploy ML Alternatives in 2026
Looking for something like Hands-on Train and Deploy ML? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 10 are open source.
This tutorial walks through training and deploying a machine learning REST API that predicts cryptocurrency prices in ten steps.
Top picks at a glance
Quick comparison
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Machine Learning Visualized | — | Yes | — |
| 2 | Handson ML3 | — | Yes | — |
| 3 | rasbt/LLMs-from-scratch | — | Not stated | — |
| 4 | ML Engineering | — | Not stated | — |
| 5 | Learn-Python | — | Yes | — |
| 6 | Machine Learning Roadmap | — | Not stated | Web |
| 7 | Codecademy's Data Science | — | Not stated | Web |
| 8 | Data Science Ipython Notebooks | — | Not stated | — |
| 9 | ML YouTube Courses | — | Yes | — |
| 10 | Sourcecodester | — | Not stated | Web |
All Hands-on Train and Deploy ML alternatives
A series of Jupyter notebooks teaches machine learning and deep learning in Python with Scikit-Learn, Keras, and TensorFlow.
rasbt/LLMs-from-scratch
github.com/rasbt/LLMs-from-scratchThis repository walks through implementing a ChatGPT like language model in PyTorch, step by step.
ML Engineering
github.com/stas00/ml-engineeringThis open book collects methods, tools, and instructions for training, fine-tuning, and running machine learning models.
A Python learning playground and cheat sheet organizes example scripts by topic, with explanations for the code.
Machine Learning Roadmap
rentry.org/machine-learning-roadmapThis machine learning roadmap lays out a learning path that starts with mathematics and calculus fundamentals.
Codecademy's Data Science
codecademy.com/learn/paths/data-scienceCodecademy’s Machine Learning Specialist path covers Python, SQL, pandas, scikit-learn, Matplotlib, and TensorFlow.
Data Science Ipython Notebooks
github.com/donnemartin/data-science-ipython-no…Data Science IPython Notebooks collects notebooks about data science, including TensorFlow deep learning.
A curated repository helps readers discover machine learning and AI courses published on YouTube.
Sourcecodester
sourcecodester.comSourcecodester publishes free source code projects and tutorials in programming languages including Python, PHP, and Java.
Tpoint Tech
tpointtech.comTpoint Tech publishes free online tutorials and interview questions across programming languages and technology subjects.
ItSourceCode
itsourcecode.comItSourceCode offers free source code, capstone projects, and programming tutorials in several languages.
Virgilio
github.com/virgili0/VirgilioAn open-source initiative, Virgilio guides learners through data science resources and skill development.
Scipy Lectures
lectures.scientific-python.orgScientific Python Lectures is a set of learning materials about Python for scientific computing.
IAILab
iailab.kaist.ac.kr/teaching/deep-learningThe iAI KAIST page shares deep learning materials that visitors are permitted to use, modify, and distribute.
Virgilio
virgili0.github.io/VirgilioVirgilio organizes data science e-learning resources in a structured project overview.
This LLM course combines learning roadmaps with Google Colab notebooks for studying large language models.
Algorithms Cheatsheet Resources collects reference material for programming and algorithms.
Awesome YouTubers collects channels that teach a range of subjects through video.
A curated list collects tutorials that teach programming through building projects.
AI for Beginners is a Microsoft course organized as 24 lessons across 12 weeks.
This repository documents a 90-day cybersecurity study plan with topics for a staged learning schedule.
Machine Learning for Software Engineers
github.com/ZuzooVn/machine-learning-for-softwa…A daily study plan for people working toward becoming machine learning engineers.
ML Course Notes
github.com/dair-ai/ML-Course-NotesA collaborative collection shares course and lecture notes on machine learning, natural language processing, and AI.
Alternatives to similar tools
What is the best alternative to Hands-on Train and Deploy ML?
Are there open-source alternatives to Hands-on Train and Deploy ML?
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