We built an online resource for scientists studying human behavior to understand and apply new methods, concepts, and techniques from machine-learning, AI, and other computational fields. Many online data-science resources target workers in industry, programmers, and other communities with extensive technical expertise. This library curates resources useful to those who study cognition, perception, action, language, neuroscience, social interactions, and other aspects of human behavior. Feel free to peruse, consume and even contribute: Data Science & Behavioral Library
We highly recommend reading this Contribution Guide if you want to publish resources on this site.
This online portal has resources for 11 topic families (listed below) and over 80 data science topics: Table of Topics
- INTRO TO DATA SCIENCE
- NATURAL LANGUAGE PROCESSING
- CLASSIFICATION AND REGRESSION
- MODEL FITTING AND REGULARIZATION
- TOOLS FOR DATA SCIENCE
- DATA REDUCTION
- NEURAL NETWORKS
- CATEGORIZATION AND INFERENCE
- REINFORCEMENT LEARNING
- TIME SERIES
- NETWORK AND GRAPHS
These resources are hosted on github, and while exploring this site you might find these icons as an invitation to contribute your expertise:
- 🆘 = Topic requires contributors to add content!
- 🚧 = Topic requires contributors to edit the existing content.
- ✋ = Suggest a topic or provide us feedback.
Please don’t miss out on the chance for us to thank you for your efforts and highlight your work! If you contribute to this site, please include yourself in our About the Authors page!
We could not have created this excellent resource without the guidance of and great idea from Prof. Tim Rogers, the wizardry and infrastructure expertise of Pablo Caceres, and the frontend user experience and content expertise of Kushin Mukherjee, content edits from Caitlin Iverson, and enthusiastic contributions from LUCID trainees, NRT trainees and our community!