9.1: Genetic Algorithm: Introduction - The Nature of Code
Welcome to part 1 of a new series of videos focused on Evolutionary Computing, and more specifically, Genetic Algorithms. In this tutorial, I introduce the concept of a genetic algorithm, how it can be used to approach "search" problems and how it relates to brute force algorithms. 🎥 Next
From playlist Session 2 - Genetic Algorithms - Intelligence and Learning
9.2: Genetic Algorithm: How it works - The Nature of Code
In part 2 of this genetic algorithm series, I explain how the concepts behind Darwinian Natural Selection are applied to a computational evolutionary algorithm. 🎥 Previous video: https://youtu.be/9zfeTw-uFCw?list=RxTfc4JLYKs&list=PLRqwX-V7Uu6bJM3VgzjNV5YxVxUwzALHV 🎥 Next video: https://yo
From playlist Session 2 - Genetic Algorithms - Intelligence and Learning
Machine Learning Control: Genetic Algorithms
This lecture provides an overview of genetic algorithms, which can be used to tune the parameters of a control law. Machine Learning Control T. Duriez, S. L. Brunton, and B. R. Noack https://www.springer.com/us/book/9783319406237 Closed-Loop Turbulence Control: Progress and Challenges
From playlist Data-Driven Control with Machine Learning
Continuous Genetic Algorithm - Part 1
This video is about Continuous Genetic Algorithm - Part 1
From playlist Optimization
Build a Heap - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Binary Genetic Algorithm - Part 1: Introduction
This video is about Binary Genetic Algorithm - Part 1: Introduction
From playlist Optimization
Genes, Patents, and Race: The History of Science as a Bridge Between Disciplines
https://www.ias.edu/events/publiclecture-october2018 More videos on http://video.ias.edu
From playlist Historical Studies
Data Science - Part XIV - Genetic Algorithms
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview on biological evolution and genetic algorithms in a machine learning context. W
From playlist Data Science
Building Generating Functions for Sequences Using Differencing
This video explains how to build generating functions for various sequences using the technique of differencing. mathispower4u.com
From playlist Additional Topics: Generating Functions and Intro to Number Theory (Discrete Math)
The Master Algorithm | Pedro Domingos | Talks at Google
Machine learning is the automation of discovery, and it is responsible for making our smartphones work, helping Netflix suggest movies for us to watch, and getting presidents elected. But there is a push to use machine learning to do even more—to cure cancer and AIDS and possibly solve ev
From playlist AI talks
Fuzzy Logic Systems - Part 6: Three Fuzzy Inference Systems
This video is about Fuzzy Logic Systems - Part 6: Three Fuzzy Inference Systems
From playlist Fuzzy Logic
Program Summer Research Program on Dynamics of Complex Systems ORGANIZERS: Amit Apte, Soumitro Banerjee, Pranay Goel, Partha Guha, Neelima Gupte, Govindan Rangarajan and Somdatta Sinha DATE : 15 May 2019 to 12 July 2019 VENUE : Madhava hall for Summer School & Ramanujan hall f
From playlist Summer Research Program On Dynamics Of Complex Systems 2019
16. Protein Interaction Networks
MIT 7.91J Foundations of Computational and Systems Biology, Spring 2014 View the complete course: http://ocw.mit.edu/7-91JS14 Instructor: Ernest Fraenkel This lecture by Prof. Ernest Fraenkel is on protein interaction networks. He covers network models, including their structure and an an
From playlist MIT 7.91J Foundations of Computational and Systems Biology
Probabilistic Graphical Models (PGMs) In Python | Graphical Models Tutorial | Edureka
🔥 Post Graduate Diploma in Artificial Intelligence by E&ICT Academy NIT Warangal: https://www.edureka.co/executive-programs/machine-learning-and-ai This Edureka "Graphical Models" video answers the question "Why do we need Probabilistic Graphical Models?" and how are they compare to Neural
From playlist Machine Learning Algorithms in Python (With Demo) | Edureka
Binary Genetic Algorithm - Part 2: Working Principle and Coding/Encoding Processes
This video is about Binary Genetic Algorithm - Part 2: Working Principle and Coding/Encoding Processes
From playlist Optimization
Jere Koskela: Inference for coalescent and diffusion models in genetic (1/3)
Abstract: Mathematical models in population genetics frequently come in pairs: a diffusion process describes the forward-in-time evolution of allele frequencies in a population, and a branching-coalescing particle system describes the random genetic ancestry of a sample on sequences from t
From playlist Summer School on Stochastic modelling in the life sciences
Using Genetic Algorithms for Network Intrusion Detection and Integration into nProbe
From Ignite at OSCON 2010, a 5 minute presentation by Bill Lavender: SNORT is popular Network Intrusion Detection System (NIDS) tool that currently uses a custom rule based system to identify attacks. This presentation emphasizes on writing the algorithm to write generate the rules through
From playlist Ignite OSCON 2010
Richard Hennig: "Machine-learning for materials and physics discovery through symbolic regressio..."
Machine Learning for Physics and the Physics of Learning 2019 Workshop I: From Passive to Active: Generative and Reinforcement Learning with Physics "Machine-learning for materials and physics discovery through symbolic regression and kernel methods" Richard Hennig - University of Florida
From playlist Machine Learning for Physics and the Physics of Learning 2019
Optimal Component Selection Using the Mixed-Integer Genetic Algorithm
Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Use the mixed-integer genetic algorithm to solve an engineering design problem. For more videos, visit http://www.mathworks.com/products/global-optimization/examples.html
From playlist Math, Statistics, and Optimization