Learning AI is really easy Ⅰ- A preliminary exploration of machine learning-from understanding AI to Kaggle competition
Chapter 1 Opening the Door to AI Artificial Intelligence
1-1 WOW! Amazing artificial intelligence
1-2 Why? Everyone must learn to be the master of AI
1-3 What? AI Quick Questions and Answers
1-4 Why can machines learn like humans?
1-5 Quick Draw! Draw it and you will understand!
1-6 Summary
Chapter 2 I can also build machine learning
2-1 Five major processes of machine learning
2-2 Summary
Chapter 3: Hands-on supervised learning
3-1 Regression and Classification
3-2 Predicting House Prices in Seconds—Introduction and Application of Linear Regression
3-3 What is the probability of breast cancer? - Introduction and application of KNN classifier
3-4 Who has a higher chance of survival, Jack or Rose? - Introduction and application of decision tree classifier
3-5 Summary
Chapter 4: Hands-on Unsupervised Learning
4-1 Basic Introduction and Application of K-means Algorithm
4-2 Iris Clustering - K-means Application Example
4-3 Handwritten digit clustering - K-means application example
4-4 Summary
Chapter 5: International AI Competition
5-1 Introduction to Kaggle
5-2 Introduction to Classic Events
5-3 Kaggle data upload and ranking
5-4 Summary
Appendix A Python Basic Syntax Query Table
A-1 Basic Python concepts
Appendix B Introduction to using Google Colab
B-1 Introduction to Google Colaboratory
B-2 Notebook Configuration Settings
B-3 View the current Python version and package list