rasbt/MachineLearning-QandAI-book
An educational book by Sebastian Raschka covering advanced machine learning and AI topics including transformers, LLMs, and deep learning.
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The Machine Learning Q and AI book provides supplementary materials in the form of Jupyter Notebooks covering 30 essential questions in ML and AI. Topics include multi-GPU training paradigms, transformer fine-tuning, encoder versus decoder-style LLMs, vision transformers, and confidence intervals for machine learning. The book targets practitioners who have already locked down ML basics and want to address lingering knowledge gaps through short, focused chapters with diagrams and references.
Frequently asked
- What is rasbt/MachineLearning-QandAI-book?
- An educational book by Sebastian Raschka covering advanced machine learning and AI topics including transformers, LLMs, and deep learning.
- Is MachineLearning-QandAI-book open source?
- Yes — rasbt/MachineLearning-QandAI-book is open source, released under the BSD-3-Clause license.
- What language is MachineLearning-QandAI-book written in?
- rasbt/MachineLearning-QandAI-book is primarily written in Jupyter Notebook.
- How popular is MachineLearning-QandAI-book?
- rasbt/MachineLearning-QandAI-book has 933 stars on GitHub.
- Where can I find MachineLearning-QandAI-book?
- rasbt/MachineLearning-QandAI-book is on GitHub at https://github.com/rasbt/MachineLearning-QandAI-book.