Looking for something like The 100-Page Language Models Book? 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 4 are open source.
The Hundred-Page Language Models Book teaches machine learning foundations, transformers, and large language models.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Andrew Ng’s Machine Learning at Stanford University | — | Not stated | Web |
| 2 | Introduction to Machine Learning with Python | — | Not stated | — |
| 3 | Machine Learning Mastery | — | Not stated | Web |
| 4 | NormConf - The Normcore Tech Conference | — | Not stated | Web |
| 5 | TutorialSearch | Free | Not stated | Web |
| 6 | Homemade Machine Learning | — | Yes | — |
| 7 | AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics | — | Yes | — |
| 8 | Prompt Engineering Lil'Log | — | Not stated | Web |
| 9 | NirDiamant/GenAI Agents | — | Not stated | — |
| 10 | Stanford CS336: Language Modeling from Scratch | — | Not stated | Web |
This Coursera course teaches supervised machine learning, regression, and classification with Python.
Notebooks and code for the book "Introduction to Machine Learning with Python".
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.
TutorialSearch searches and compares online tutorials and courses across learning platforms.
Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
This repository provides a tutorial implementation of AutoML for batch and online learning.
This Lil’Log article explains prompt engineering methods for steering autoregressive language models.
This repository contains more than 50 tutorials and implementations for generative AI agent techniques.
Stanford CS336 provides course schedules, assignments, and materials for language modeling from scratch.
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.
ML-From-Scratch shares accessible NumPy implementations of machine learning models, from linear regression to deep learning.
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.
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.
This course teaches how to build neural networks from scratch in code.
Chip Huyen writes about AI system design and bringing AI applications into production.
This repository collects tutorials and examples for learning machine learning and pattern classification.
Tutor AI answers questions, explains concepts, and helps learners follow custom learning pathways at their own pace.
This repository contains code samples for the book Neural Networks and 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.
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
