2026.01.17
Chapter 1: The AI/ML Landscape & Foundational Math
Learn the basics of AI/ML and foundational math with practical examples in Python.
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2026.01.17
Chapter 2: Python for AI/ML: A Deep Dive
Learn the basics of Python for AI/ML, setting up an environment and understanding core concepts.
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Chapter 3: Data Science Toolkit: NumPy, Pandas, Matplotlib
Learn the essential libraries for data science: NumPy, Pandas, and Matplotlib. Understand their core functionalities and why they are indispensable.
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Chapter 5: Your First Steps with Python: The Language of AI
Learn Python basics and set up your environment to start building AI applications.
ACCESS_FILE >>2026.01.26
Chapter 17: Project: Archiving Machine Learning Tensors
Learn how to use OpenZL for efficient archiving and compression of ML tensors.
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Data Manipulation and Analysis: NumPy, Pandas, and Visualization for AI
A comprehensive guide to leveraging NumPy, Pandas, Matplotlib, and Seaborn for data science, from foundational concepts to advanced techniques, with a …
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