Artificial Intelligence

Artificial Intelligence#

Table of Contents#

Sections#

Resources#

  • [ h ][ w ] Hugging Face

  • [ h ][ w ] Numerai

  • [ h ][ w ] OpenAI

    • [ h ][ g ] OpenAI Gym

jonkrohn/ML-foundations

Programming neural nets from scratch in python#

YouTube#

  • [ y ] 03-16-2020. Digital Learning Hub - Imperial College London. “Mathematics for Machine Learning - Linear Algebra”.

  • [ y ] 05-09-2022. Visually Explained. “The Kernel Trick in Support Vector Machine (SVM)”.

  • [ y ] 11-25-2023. Yannic Kilcher. “What is Q-Learning (back to basics)”.

Eli the Computer Guy

  • [ y ] 01-25-2024. “Machine Learning with OpenAI API and Relational Database (OpenAI, Python, SQLite)”.

freeCodeCamp

  • [ y ] 12-04-2023. “MLOps Course - Build Machine Learning Production Grade Projects”.

My Lesson

  • [ y ] 08-09-2021. “Mathematics for Machine Learning Tutorial (3 Complete Courses in 1 video)”.

Steve Bunton.

  • [ y ] 05-29-2024 “Physics Informed Neural Networks (PINNs) [Physics Informed Machine Learning]”.

  • [ y ] 01-05-2024. “A Neural Network Primer”.

  • [ y ] 12-29-2023. “A Machine Learning Primer: How to Build an ML Model”.

  • [ y ] 01-27-2020. “Principal Component Analysis (PCA)”.

more

  • [ y ] 03-31-2024. Artem Kirsanov. “The Most Important Algorithm in Machine Learning”.

  • [ y ] 07-04-2021. Adian Liusie. “Intuitively Understanding the Cross Entropy Loss”.

  • [ y ] 08-11-2022. Asianometry. “Running Neural Networks on Meshes of Light”.

  • [ y ] 06-01-2023. Jousef Murad LITE. “Physics-Informed Neural Networks (PINNs) - An Introduction - Ben Moseley | The Science Circle”.

online

Texts#

[ h ][ w ] Russell, Stuart & Peter Norvig. (2020). Artificial Intelligence: A Modern Approach. 4th Ed. Pearson.

[ h ] Tan, Pang-Ning et al. (2017). Introduction to Data Mining. 2nd Ed. Pearson. R code.

2021 Chollet, François. Deep Learning with Python. 2e. Manning.

[ h ] 2024 Bishop, Christopher & Hugh Bishop. Deep Learning: Foundations and Concepts. Springer

  • Nelson, Hala. (2022). Essential Math for AI: Next-Level Mathematics for Developing Efficient and Successful AI Systems. O’Reilly.

  • Nield, Thomas. (2022). Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics. O’Reilly.

  • [ g ] Vaughan, Daniel. (2020). Analytical Skills for AI and Data Science: Building Skills for an AI-Driven Enterprise. O’Reilly.

  • Zhang, Xian-Da. (2020). A Matrix Algebra Approach to Artificial Intelligence. Springer.

  • [ g ] Lanham, Michael. (2020). Practical AI on the Google Cloud Platform: Utilizing Google’s State-of-the-Art AI Cloud Services. O’Reilly.

  • Nielsen, Aileen. (2020). Practical Fairness: Achieving Fair and Secure Data Models. O’Reilly.

  • Thomas, Rob & Paul Zikopoulos. (2020). The AI Ladder: Accelerate Your Journey to AI. O’Reilly.

Figures#

  • [ w ] Bostrom, Nick (1973-)

  • [ w ] Clarke, Arthur C. (1917-2008)

  • [ w ] Goertzel, Ben (1966-)

  • [ w ] Hinton, Geoffrey (1947-)

  • [ w ] Hutter, Marcus (1967-)

  • [ w ] Kubrick, Stanley (1928-1999)

  • [ w ] Kurzweil, Ray (1948-)

  • [ w ] Lenat, Douglas (1950-2023)

  • [ w ] McCarthy, John (1927-2011)

  • [ w ] Minsky, Marvin (1927-2016)

  • [ w ] Moravec, Hans (1948-)

  • [ w ] Newell, Allen (1927-1992)

  • [ w ] Ng, Andrew (1976-)

  • [ w ] Norvig, Peter (1956-)

  • [ w ] Russell, Stuart (1962-)

  • [ w ] Searle, John (1932-)

  • [ w ] Simon, Herbert (1916-2001)

  • [ w ] Turing, Alan (1912-1954)

Terms#

  • [ w ] AI Alignment

  • [ w ] AI Completeness

  • [ w ] AI History

  • [ w ] AI Progress

  • [ w ] AI Timeline

  • [ w ][ i ] AI Winter

  • [ w ] AIXI

  • [ w ] Artificial Consciousness (AC)

  • [ w ][ s ][ i ] Artificial Intelligence (AI)

  • [ w ] Artificial General Intelligence (AGI)

  • [ w ] Automated Reasoning

  • [ w ] Chinese Room

  • [ w ] Computational Graph

  • [ w ] Computational Learning Theory

  • [ w ] Connectionism

  • [ w ] Cyc

  • [ w ][ i ] Data Mining

  • [ w ] DeepMind (Google)

  • [ w ] Expert System

  • [ w ] General Game Playing (GGP)

  • [ w ] Hard Problem of Consciousness

  • [ w ] Inference Engine

  • [ w ] Intelligence

  • [ w ] Intelligent Agent

  • [ w ] Knowledge Base (KB)

  • [ w ][ i ] Knowledge Engineering

  • [ w ] Knowledge Representation and Reasoning (KRR)

  • [ w ] Large Language Model (LLM)

  • [ w ][ s ] Logic-based AI

  • [ w ] Neural Turing Machine (NTM)

  • [ w ] Neuroinformatics

  • [ w ] Ontology

  • [ w ] Philosophy of Artificial Intelligence

  • [ w ] Reinforcement Learning (RL)

  • [ w ] Soar

  • [ w ][ i ] Strong AI

  • [ w ] Superintelligence

  • [ w ] Symbolic AI

  • [ w ] Symbol Grounding Problem

  • [ w ][ s ][ i ] Turing Test

  • [ w ][ i ] Weak AI

  • [ w ] Whole Brain Emulation

  • [ w ] Depth-First Search (DFS)

  • [ w ] Evolutionary Algorithm (EA)

  • [ w ] Evolutionary Computation

  • [ w ] Genetic Algorithm (GA)

Contents