If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Machine Learning
In this video, you’ll learn more about the evolution of machine learning and its impact on daily life. Visit https://www.gcflearnfree.org/thenow/what-is-machine-learning/1/ for our text-based lesson. This video includes information on: • How machine learning works • How machine learning i
From playlist Machine Learning
(ML 1.1) Machine learning - overview and applications
Attempt at a definition, and some applications of machine learning. A playlist of these Machine Learning videos is available here: http://www.youtube.com/my_playlists?p=D0F06AA0D2E8FFBA
From playlist Machine Learning
Machine learning describes computer systems that are able to automatically perform tasks based on data. A machine learning system takes data as input and produces an approach or solution to a task as output, without the need for human intervention. Machine learning is closely tied to th
From playlist Data Science Dictionary
Introduction To Machine Learning | Machine Learning Basics for Beginners | ML Basics | Simplilearn
Machine Learning is a trending topic nowadays. This Introduction to Machine Learning video will help you to understand what is Machine Learning, importance of Machine Learning, advantages and disadvantages of Machine Learning, what are the types of Machine Learning - supervised, unsupervis
What Is Machine Learning? | What Is Machine Learning And How Does It Work? | Simplilearn
This Machine Learning tutorial will help you understand what is Machine Learning, Artificial Intelligence vs Machine Learning vs Deep Learning, how does Machine Learning work, types of Machine Learning, Machine Learning pre-requisites and applications of Machine Learning. Machine learning
Machine Learning: Zero to Hero
This is a talk for people who know code, but who don’t necessarily know machine learning. Learn the ‘new’ paradigm of machine learning, and how models are an alternative implementation for some logic scenarios, as opposed to writing if/then rules and other code. This session will guide you
From playlist Machine Learning
Machine learning is all around us; on our phones, powering social networks, helping the police and doctors, scientists and mayors. But how does it work? In this animation we take a look at how statistics and computer science can be used to make machines that learn. Visit www.oxfordsparks
From playlist Machine Learning
This lecture provides an overview of machine learning, and how it fits into this introductory video sequence on data science. We discuss how machine learning involves "modeling with data". Book website: http://databookuw.com/ Steve Brunton's website: eigensteve.com
From playlist Intro to Data Science
Nature Reviews Physics: Machine learning in theoretical and experimental high energy physics
Machine learning has been used in experimental high energy physics since the 1990s, later enabling the data analysis that made possible the discovery of the Higgs boson. Today machine learning is not only an integral part of the data acquisition and analysis workflows in high energy physic
From playlist Nature Reviews Physics - AI for science and government (ASG) series
Machine Learning in Environmental Science and Prediction: An Overview | AISC
For slides and more information on the paper, visit https://ai.science/e/machine-learning-in-environmental-science-and-prediction-an-overview--sBSFNhGyawkmyoLeFBks Speaker: Andre Erler; Host: Peetak Mitra; Discussion Facilitator: Amir Feizpour Motivation: This presentation is the debut
From playlist ML in Environmental Science
Discrepancy Modeling with Physics Informed Machine Learning
This video describes how to combine machine learning with classical physics models to correct for discrepancies in the data (e.g., from nonlinear friction, wind resistance, etc.). Several examples are covered, from modern robotics, to classical connections with Galileo v. Aristotle, and K
From playlist Research Abstracts from Brunton Lab
Battery Modelling using Data-Driven Machine Learning | AISC
For slides and more information on the paper, visit https://ai.science/e/battery-modelling-using-data-driven-machine-learning--L8eQwA8StCpd3Lsh0OGK Speaker: Gareth Conduit; Host: Sajeda Mokbel Motivation: In the field of energy storage, machine learning has recently emerged as a promisi
From playlist ML for Physics
Steps towards more human-like learning in machines - Josh Tenenbaum
More videos on http://video.ias.edu
From playlist Mathematics
Ep 1: Stanford PhD student Joseph Bakarji on Machine Learning and the Hard Sciences
Broadcasted live on Twitch -- Watch live at https://www.twitch.tv/formalsystem
From playlist Interviews
Machine Learning for Computational Fluid Dynamics
Machine learning is rapidly becoming a core technology for scientific computing, with numerous opportunities to advance the field of computational fluid dynamics. This paper highlights some of the areas of highest potential impact, including to accelerate direct numerical simulations, to i
From playlist Data Driven Fluid Dynamics
Tristan Bereau: "Physics in and out of machine learning for molecular simulations: priors and pr..."
Machine Learning for Physics and the Physics of Learning 2019 Workshop II: Interpretable Learning in Physical Sciences "Physics in and out of machine learning for molecular simulations: priors and predictive constraints" Tristan Bereau - Max Planck Institute for Polymer Research, Theory G
From playlist Machine Learning for Physics and the Physics of Learning 2019
Nature Reviews Physics: Machine learning in condensed matter and materials physics
Machine learning methods are now used in the simulation of the building blocks of matter: from the electronic- to the molecular-level structure. These tools have boosted well-known computational methods such as density functional theory or molecular dynamics simulation. These are expected
From playlist Nature Reviews Physics - AI for science and government (ASG) series
"Microscopy is all you need" - Sergei Kalinin
This webinar is presented by Dr. Sergei Kalinin, corporate fellow at the Center for Nanophase Materials Sciences at Oak Ridge National Laboratory and Associate Professor at the Department of Materials Science and Engineering at the University of Tennessee-Knoxville. Sergei discusses how m
From playlist Materials Informatics
Machine Learning with scikit learn Part Two | SciPy 2017 Tutorial | Andreas Mueller & Alexandre Gram
Tutorial materials found here: https://scipy2017.scipy.org/ehome/220975/493423/ Machine learning is the task of extracting knowledge from data, often with the goal of generalizing to new and unseen data. Applications of machine learning now touch nearly every aspect of everyday life, fro
From playlist talks