Neural Networks and Deep Learning
github.com/mnielsen/neural-networks-and-deep-l…This repository contains code samples for the book Neural Networks and Deep Learning.
Looking for something like Spinning Up? Here are 14 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 1 are free or have a free plan and 4 are open source.
Spinning Up provides documentation and learning resources for deep reinforcement learning.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Neural Networks and Deep Learning | — | Not stated | — |
| 2 | Andrew Ng’s Machine Learning at Stanford University | — | Not stated | Web |
| 3 | The 100-Page Language Models Book | — | Not stated | Web |
| 4 | Machine Learning Mastery | — | Not stated | Web |
| 5 | NormConf - The Normcore Tech Conference | — | Not stated | Web |
| 6 | TutorialSearch | Free | Not stated | Web |
| 7 | Neural Networks: Zero to Hero | — | Not stated | Web |
| 8 | Homemade Machine Learning | — | Yes | — |
| 9 | Introduction to Machine Learning with Python | — | Not stated | — |
| 10 | AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics | — | Yes | — |
This repository contains code samples for the book Neural Networks and Deep 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.
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.
This course teaches how to build neural networks from scratch in code.
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 provides a tutorial implementation of AutoML for batch and online learning.
The OpenAI Cookbook provides examples and guides for using the OpenAI API.
This repository contains more than 50 tutorials and implementations for generative AI agent techniques.
Aman’s AI Journal collects seminal research papers and course notes for artificial intelligence and deep learning.
ML-From-Scratch shares accessible NumPy implementations of machine learning models, from linear regression to deep learning.
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