Resources
From AI Matters Wiki
Revision as of 09:26, 23 August 2017 by ToddNeller (Talk | contribs) (→Neural Network Learning: adding links)
Starting Places
General
Machine Learning
- Texts:
- Christopher Bishop. Pattern Recognition and Machine Learning
- Kevin Murphy. Machine Learning: A Probabilistic Perspective
- David Barber. Probabilistic Reasoning and Machine Learning (Barber's free PDF version)
- Tom Mitchell. Machine Learning
- Ethem Alpaydin. Introduction to Machine Learning
- Statistical Learning:
- Reinforcement Learning:
- Online resources:
- Andrew Ng's free online Coursera Machine Learning course
- UC Irvine Machine Learning Repository
- Kaggle datasets
- RStudio software for labs
- Weka Java-based Data Mining software and Ian Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques
- Model AI Assignments
- Berkeley student crash course on ML
- Recommendations:
Neural Network Learning
- Textbooks
- Websites
- Waikit Lau and Arthur Chan's Artificial Intelligence and Deep Learning (AIDL) Facebook group and FAQ
- A Guide to Deep Learning by YerevaNN Labs
- Piotr Migdał's Learning Deep Learning with Keras
- a16z team's reference links
- Stanford's CS 231n Convolutional Networks course website
- various Wikipedia pages concerning artificial neural networks
- TensorFlow Playground
- Why Momentum Really Works
- Online Courses
- Software
- Hardware