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.
概览
收录于
2026年3月17日
学科与领域
computer-science-advanced · data-science-analytics
年级范围
九年级（高一）–十二年级（高四）
页面类型
Course
简介
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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