Looking for something like pattern classification? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 3 are free or have a free plan and 5 are open source.
This repository collects tutorials and examples for learning machine learning and pattern classification.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics | — | Yes | — |
| 2 | Homemade Machine Learning | — | Yes | — |
| 3 | ML-From-Scratch | — | Yes | — |
| 4 | NirDiamant/GenAI Agents | — | Not stated | — |
| 5 | Andrew Ng’s Machine Learning at Stanford University | — | Not stated | Web |
| 6 | AI Expert Roadmap | — | Yes | — |
| 7 | Introduction to Machine Learning with Python | — | Not stated | — |
| 8 | Weka | — | Not stated | Web |
| 9 | TutorialSearch | Free | Not stated | Web |
| 10 | StepByStepML | Free | Not stated | Web |
This repository provides a tutorial implementation of AutoML for batch and online learning.
Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
ML-From-Scratch shares accessible NumPy implementations of machine learning models, from linear regression to deep learning.
This repository contains more than 50 tutorials and implementations for generative AI agent techniques.
This Coursera course teaches supervised machine learning, regression, and classification with Python.
This repository provides a roadmap to becoming an artificial intelligence expert.
Notebooks and code for the book "Introduction to Machine Learning with Python".
Weka 3 provides open source machine learning and data mining software written in Java.
TutorialSearch searches and compares online tutorials and courses across learning platforms.
Free online machine learning calculators. Input your dataset and watch algorithms like K-Means, Minimax, and KNN get solved step-by-step for CS exams.
The Hundred-Page Language Models Book teaches machine learning foundations, transformers, and large language models.
Machine Learning Mastery shares guidance for developers learning to apply machine learning.
Normconf is the tech conference about all the stuff that matters in data and machine learning, but doesn.
Made With ML offers lessons on designing, developing, deploying, and improving production machine learning applications.
MLU-Explain provides visual explanations of machine learning concepts through educational materials.
Udacity’s Introduction to Machine Learning course covers foundational machine learning and data analysis.
The ICML site provides information about the International Conference on Machine Learning in Lille.
Tutor AI answers questions, explains concepts, and helps learners follow custom learning pathways at their own pace.
Stanford CS336 provides course schedules, assignments, and materials for language modeling from scratch.
Azure for Students provides cloud services, developer tools, and credits for building apps and exploring AI.
Chip Huyen writes about AI system design and bringing AI applications into production.
The OpenAI Cookbook provides examples and guides for using the OpenAI API.
R-bloggers collects R news and tutorials written by bloggers from across the community.
This repository contains code samples for the book Neural Networks and Deep Learning.
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
