Everything AI/ML
viveknaskar.github.io/everything-ai-mlThis curated AI and machine learning guide organizes over 228 learning resources across 30 sections.
Looking for something like Everything AI Ml? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 1 are free or have a free plan and 8 are open source.
A curated collection gathers learning resources for generative AI, machine learning, LLMs, RAG, and related topics.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Everything AI/ML | — | Not stated | Web |
| 2 | Learn Gamedev | — | Yes | — |
| 3 | Professional Programming | — | Yes | — |
| 4 | Hackr.io | — | Not stated | Linux, Web |
| 5 | Programming Learning Index | — | Yes | — |
| 6 | Ebook Foundation | — | Not stated | Web |
| 7 | ProgrammingLearningResources | — | Not stated | Linux, Web |
| 8 | ML YouTube Courses | — | Yes | — |
| 9 | Machine Learning for Software Engineers | — | Not stated | — |
| 10 | ML Course Notes | — | Not stated | — |
This curated AI and machine learning guide organizes over 228 learning resources across 30 sections.
A curated collection of resources supports learning game development, from introductory material to further study.
This repository curates learning resources for software engineers, including material for people exploring programming topics.
Hackr.io catalogs technology courses, projects, user-submitted resources, and learning topics.
This repository lists freely available learning resources across programming, mathematics, and science.
The Ebook Foundation's free-programming-books repository lists freely available learning resources in many languages.
This programming learning resource organizes links by language and subject, including web development, databases, and game development.
A curated repository helps readers discover machine learning and AI courses published on YouTube.
A daily study plan for people working toward becoming machine learning engineers.
A collaborative collection shares course and lecture notes on machine learning, natural language processing, and AI.
Jupyter notebooks implement and derive machine learning algorithms from first principles using NumPy.
This tutorial walks through training and deploying a machine learning REST API that predicts cryptocurrency prices in ten steps.
Mallet provides machine learning tools for language processing, according to its project title.
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A series of Jupyter notebooks teaches machine learning and deep learning in Python with Scikit-Learn, Keras, and TensorFlow.
This open book collects methods, tools, and instructions for training, fine-tuning, and running machine learning models.
ProjectLearn teaches programming through projects across web, mobile, game development, machine learning, and artificial intelligence.
Machine Learning Visualized organizes its material as a collection of visual learning resources in a repository.
StrataScratch offers over 1,000 data science interview questions across SQL, Python, statistics, machine learning, and data projects.
Machine Learning Systems is a two-volume textbook about how machine learning systems are built, covering the engineering behind AI.
Deep-ML provides hands-on exercises in machine learning and data science fundamentals.
Learn AI From Scratch presents a draft curriculum covering foundational topics for building an understanding of artificial intelligence.
This machine learning roadmap lays out a learning path that starts with mathematics and calculus fundamentals.
Codecademy’s Machine Learning Specialist path covers Python, SQL, pandas, scikit-learn, Matplotlib, and TensorFlow.
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