Foundations Of Machine Learning
✅ A must read book for machine learning researchers

It mainly discusses the mathematical background of machine learning algorithms.

Python Crash Course
A comprehensive approach to programming
🐍 with Python
✅ For Beginners

Dive into Deep Learning (D2L Book)

Dive into Deep Learning: an interactive deep learning book with code, math, and discussions, based on the NumPy interface

https://github.com/d2l-ai/d2l-en
#deep_learning

Necessity of complex numbers in Quantum Mechanics

https://www.youtube.com/watch?v=f079K1f2WQk
#mathematics #quantum_physics

A great discussion with Sebastian Thrun about various topics such as: Flying Cars, Autonomous Vehicles, and Education

https://www.youtube.com/watch?v=ZPPAOakITeQ
#self_driving_cars #education #artificial_intelligence #machine_learning

An Overview of Recent State of the Art Deep Learning Algorithms/Architectures

Lecture on most recent research and developments in deep learning, and hopes for 2020. This is not intended to be a list of SOTA benchmark results, but rather a set of highlights of machine learning and AI innovations and progress in academia, industry, and society in general. This lecture is part of the MIT Deep Learning Lecture Series.

https://www.youtube.com/watch?v=0VH1Lim8gL8&t=999s
#deep_learning #artificial_intelligence

A fruitful relationship between neuroscience and AI

https://deepmind.com/blog/article/Dopamine-and-temporal-difference-learning-A-fruitful-relationship-between-neuroscience-and-AI
#reinforcement_learning #machine_learning #neuroscience #artificial_intelligence

Neural Architecture Search for Transformers

In summary, they employed an evolutionary algorithm, with a novel encoding scheme, to search for an optimal transformer architecture.

https://www.youtube.com/watch?v=khA-fiC1Wa0&feature=youtu.be

A Fascinating Philosophical Discussion about the Nature of Consciousness


https://www.youtube.com/watch?v=LW59lMvxmY4
#philosophy #consciousness

Book: The SOAR Cognitive Architecture

Introduction: in development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements.

https://dl.acm.org/doi/book/10.5555/2222503
#cognitive_science #neuroscience #reinforcement_learning #artificial_intelligence

Model Predictive Control: Powerful Optimization Strategy for Feedback Control

https://www.youtube.com/watch?v=YwodGM2eoy4
#optimization

Complete Statistical Theory of Learning

https://www.youtube.com/watch?v=Ow25mjFjSmg
#statistics #machine_learning
#theory

https://t.co/fHiVaFDere?amp=1
#AI #machine_learning #education

Artificial Intelligence from Perspective of Philosophers

https://plato.stanford.edu/entries/artificial-intelligence/
#AI #philosophy #history

Reinforcement learning and Optimal Control (Draft version)

Desperately looking for the original version of this book. If you could find it, please let me know.
#reinforcement_learning #optimal_control

Deep Reasoning Papers

A repository which contains recent papers including Neural Symbolic Reasoning, Logical Reasoning, Visual Reasoning, natural language reasoning and any other topics connecting deep learning and reasoning.

https://github.com/floodsung/Deep-Reasoning-Papers
#reasoning #deep_learning #artificial_intelligence

TensorFlow Quantum: An Open Source Library for Quantum Machine Learning

https://ai.googleblog.com/2020/03/announcing-tensorflow-quantum-open.html
#quantum_computing #machine_learning #quantum_machine_learning

The Underlying Mathematics of New Coronavirus (COVID-19) Growth

https://www.youtube.com/watch?v=Kas0tIxDvrg
#math #statistics

An overview of gradient descent optimization algorithms

Abstract: Gradient descent optimization algorithms, while increasingly popular, are often used as black-box optimizers, as practical explanations of their strengths and weaknesses are hard to come by. This article aims to provide the reader with intuitions with regard to the behaviour of different algorithms that will allow her to put them to use. In the course of this overview, we look at different variants of gradient descent, summarize challenges, introduce the most common optimization algorithms, review architectures in a parallel and distributed setting, and investigate additional strategies for optimizing gradient descent

https://arxiv.org/pdf/1609.04747.pdf
#deep_learning #optimization