Machine Learning | Google for Developers
This resource offers a comprehensive crash course in machine learning, covering fundamental regression and classification models, data handling techniques, advanced model architectures, and real-world deployment considerations. It's designed to provide learners with a solid understanding of building and deploying ML models.
Overzicht
Toegevoegd op
17 maart 2026
Vak & domein
computer-science-advanced · data-science-analytics
Schooljaar
Klas 1 (brugklas)–Klas 4
Paginatype
Course
Inleiding
Machine Learning Crash Course (MLCC) Overview
- Purpose: A practical, fast-paced introduction to machine learning provided by Google for Developers.
- Format: Includes animated videos, interactive visualizations, and hands-on practice exercises.
- History: Originally launched in 2018; recently refreshed to include recent AI advances and enhanced interactive learning.
- Structure: Self-contained modules allowing users to skip ahead or follow a recommended sequence.
- Core Curriculum:
- ML Models: Fundamentals of regression, classification, categorical data (one-hot encoding, feature hashing, mean encoding), feature crosses, and dataset preparation.
- Advanced ML Models: Introduction to Large Language Models (LLMs), covering tokens, Transformers, architecture, and training.
- Real-world ML: Best practices for productionization, automation, and responsible engineering.
- Ethics: Principles for auditing models for fairness and strategies for mitigating data bias.
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