AI-Accelerated Product Development
...
Recipe
public
Share
Star
SNAPlist 0 - Structured, Noob-friendly, Annotated, and Prioritized Lists
Collaborators
Reviewers
Total time needed:
~2 hours
See details (learning objective, target audience, etc)...
Learning Objectives
This is SNAPlist 0. A short list about SNAPlists! Where it came from, what it means, and what it tries to achieve, the science behind it!
Potential Use Cases
learning how to learn!
Target Audience
BEGINNER
all learners
Go through the following
annotated items
in order
:
WRITEUP
1. SNAPlists, the art of documenting your leaning process
What are SNAPlists?
10 minutes
WRITEUP
2. How do SNAPlists benefit you?
What can you hope to achieve with SL's that you wouldn't otherwise?
5 minutes
WRITEUP
3. Is there science behind SNAPlists?
Is this a made up thing, or is it based on some science?
10 minutes
WRITEUP
4. Show me some examples of what I can do with SNAPlists
What are some of the interesting patterns people have used to create SL's?
10 minutes
OTHER
5. Meta-cognition: learning about learning!
what is meta-cognition?
why does meta-cognition matter?
45 minutes
ARTICLE
6. Experiential Learning Theory
What is experiential learning?
What are the components of experiential learning?
5 minutes
ARTICLE
7. Zone of Proximal Development
How can one learning contextually?
5 minutes
Additional Resources...
WRITEUP
8. SNAPList FAQ
What can I do with SNAPlists?
5 minutes
Concepts Covered
Previewing stream
Science of Science
Upcoming Live Sessions
Videos
Learning Packages
Past Capstones
People
Search for a tag:
Tags list
Reinforcement Learning
ML in Cybersecurity
ML in Chemistry
Network Analysis
Synthetic Data
Generative Adversarial Networks
ML in Climate Science
ML in Biology
Computer Vision
Careers in ML
AI Ethics
AI Sustainability
ML in Biochemistry and Drug Discovery
ML Engineering and Ops
Math and Foundations
IOT and Edge Security
ML Interpretability
ML in Aerospace
Natural Language Processing
ML in Neuroscience
Founders Stream
ML in Physics
ML in Health
Science of Science
ML for Time Series
Quantum Tech and Quantum Machine Learning
Investment in Emerging Tech
ML in Material Science
Recommender Systems
Graph Neural Nets
AI Products
ML in Economics
ML in Marketing