Looking for something like TutorialSearch? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 2 are free or have a free plan and 5 are open source.
TutorialSearch searches and compares online tutorials and courses across learning platforms.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | NormConf - The Normcore Tech Conference | — | Not stated | Web |
| 2 | AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics | — | Yes | — |
| 3 | Andrew Ng’s Machine Learning at Stanford University | — | Not stated | Web |
| 4 | The 100-Page Language Models Book | — | Not stated | Web |
| 5 | Machine Learning Mastery | — | Not stated | Web |
| 6 | NirDiamant/GenAI Agents | — | Not stated | — |
| 7 | Homemade Machine Learning | — | Yes | — |
| 8 | Introduction to Machine Learning with Python | — | Not stated | — |
| 9 | pattern classification | — | Yes | — |
| 10 | Mlu github | — | Not stated | Web |
Normconf is the tech conference about all the stuff that matters in data and machine learning, but doesn.
This repository provides a tutorial implementation of AutoML for batch and online learning.
This Coursera course teaches supervised machine learning, regression, and classification with Python.
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.
This repository contains more than 50 tutorials and implementations for generative AI agent techniques.
Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
Notebooks and code for the book "Introduction to Machine Learning with Python".
This repository collects tutorials and examples for learning machine learning and pattern classification.
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.
Stanford CS336 provides course schedules, assignments, and materials for language modeling from scratch.
Chip Huyen writes about AI system design and bringing AI applications into production.
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.
Tutor AI answers questions, explains concepts, and helps learners follow custom learning pathways at their own pace.
Made With ML offers lessons on designing, developing, deploying, and improving production machine learning applications.
Weka 3 provides open source machine learning and data mining software written in Java.
ML-From-Scratch shares accessible NumPy implementations of machine learning models, from linear regression to deep learning.
Azure for Students provides cloud services, developer tools, and credits for building apps and exploring AI.
Spinning Up provides documentation and learning resources for deep reinforcement learning.
This repository provides a roadmap to becoming an artificial intelligence expert.
This course teaches how to build neural networks from scratch in code.
This repository contains code samples for the book Neural Networks and Deep Learning.
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