D2L - Introduction - 2/2

1.3.2 UnSupervised and Self-Supervised Learning

The author lists the difference between traditional software engineering and machine learning. While software engineering focuses on solving problems with rule-based solutions, machine learning(deep learning) tries to solve problems that are ambiguous and the solution can evlove by itself after seeing more examples.

1. Clustering
2. PCA
3. Relationship, Rome - Italy = France - Paris
4. causality and probabilistic graphical models

1.3.3 Interacting with an Environment

1.3.4 Reinforcement Learning

1.4 Roots

1.5 The road to deep learning

1.6 Success Stories

1.7 The essence of deep learning

Thus, one key advantage of deep learning is that it replaces not only the shallow models at the end of traditional learning pipelines, but also the labor-intensive process of feature engineering.

1.8 Summary

My takeaway

Chapter1. Introduction mainly discussed machine learning from data, definition, examples, history, current success, provided foundation to future studies.