https://github.com/casperkristiansson/elements-of-ai-building-ai
All exercises for the course Elements of AI - Building AI
https://github.com/casperkristiansson/elements-of-ai-building-ai
bayes-classifier bayes-rule building-ai deep-learning elements-of-ai hill-climbing linear-regression linear-regression-models logistic-regression machine-learning naive-bayes naive-bayes-algorithm naive-bayes-classifier nearest-neighbor-search neural-networks overfitting probability-fundamentals
Last synced: about 1 month ago
JSON representation
All exercises for the course Elements of AI - Building AI
- Host: GitHub
- URL: https://github.com/casperkristiansson/elements-of-ai-building-ai
- Owner: CasperKristiansson
- Created: 2021-02-22T21:48:57.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2022-01-13T11:07:26.000Z (over 3 years ago)
- Last Synced: 2025-04-12T13:11:32.687Z (6 months ago)
- Topics: bayes-classifier, bayes-rule, building-ai, deep-learning, elements-of-ai, hill-climbing, linear-regression, linear-regression-models, logistic-regression, machine-learning, naive-bayes, naive-bayes-algorithm, naive-bayes-classifier, nearest-neighbor-search, neural-networks, overfitting, probability-fundamentals
- Language: Python
- Homepage:
- Size: 20.5 KB
- Stars: 20
- Watchers: 1
- Forks: 26
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Elements of AI - Building AI
Building AI a flexible online course for anyone who wants to learn about the practical methods that make artificial intelligence a reality. You will get a solid introduction to for example machine learning and neural networks, and you will learn where and how AI methods are applied in real life. It is easy to move freely between the three difficulty levels, from multiple choice exercises to programming with Python – depending on whether you know programming or not. As a result of this course, you will be able to craft your own AI idea and present it to the community. Doing the online course is free of charge, but you can purchase the Building AI certificate to reward yourself for the effort.
https://buildingai.elementsofai.com/
## Chapters
### Chapter 1 - Getting Started With AI
- Why AI matters
- Optimization
- Hill climbing
### Chapter 2 - Deailing With Uncertainty
- Probaility fundamentals
- The Bayes Rule
- Native Bayers classifier
### Chapter 3 - Machine Learning
- Linear regression
- The neasest neighbor method
- Working with text
- Overfitting
### Chapter 4 - Neural Networks
- Logicistic regression
- From logistic regression to neural networks
- Deep learning
### Chapter 5 - Conclusion
- Summary
- Your AI idea
- AI idea gallery