Applied mathematics

Computational science

Computational science, also known as scientific computing or scientific computation (SC), is a field in mathematics that uses advanced computing capabilities to understand and solve complex problems. It is an area of science that spans many disciplines, but at its core, it involves the development of models and simulations to understand natural systems. * Algorithms (numerical and non-numerical): mathematical models, computational models, and computer simulations developed to solve science (e.g., biological, physical, and social), engineering, and humanities problems * Computer hardware that develops and optimizes the advanced system hardware, firmware, networking, and data management components needed to solve computationally demanding problems * The computing infrastructure that supports both the science and engineering problem solving and the developmental computer and information science In practical use, it is typically the application of computer simulation and other forms of computation from numerical analysis and theoretical computer science to solve problems in various scientific disciplines. The field is different from theory and laboratory experiments, which are the traditional forms of science and engineering. The scientific computing approach is to gain understanding through the analysis of mathematical models implemented on computers. Scientists and engineers develop computer programs and application software that model systems being studied and run these programs with various sets of input parameters. The essence of computational science is the application of numerical algorithms and computational mathematics. In some cases, these models require massive amounts of calculations (usually floating-point) and are often executed on supercomputers or distributed computing platforms. (Wikipedia).

Computational science
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Computer Science Terminology

Learn computer science terminology. We'll take a dive into understanding some of the terms used in computer science and software development. The video starts with the basics and then gets more advanced. Video from Forrest Knight. Check out his channel: https://www.youtube.com/channel/UC

From playlist Computer Science Concepts

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SketchySVD - Joel Tropp, California Institute of Technology

This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together leading researchers in the general fields of mathematics, statistics, computer science and engineering. About the event The workshop ai

From playlist Mathematics of data: Structured representations for sensing, approximation and learning

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What Is 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

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COMPUTER SCIENCE TERMINOLOGY

Welcome to part one of computer science terminology, where we take a dive into understanding some of the terms used in computer science and software development. We've started with the basics and will continue to get more complex as this series progresses. --------------------------------

From playlist Computer Science

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Deep dictionary learning approaches for image super-resolution - Pier Luigi Dragotti, Imperial

This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together leading researchers in the general fields of mathematics, statistics, computer science and engineering. About the event The workshop ai

From playlist Mathematics of data: Structured representations for sensing, approximation and learning

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What is Quantum Machine Learning?

Generative machine learning is the field of ML that focuses on generating data. If you've seen any of the realistic-looking faces on pages such as www.thispersondoesnotexist.com or www.whichfaceisreal.com, you've seen generative machine learning in action. Quantum computing is a rapidly ad

From playlist Fundamentals of Machine Learning

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Intro to Data Science: What is Data Science?

This lecture provides an overview of the various components of data science, including data collection, cleaning, and curation, along with visualization, analysis, and machine learning (i.e. building models with data). These will be some of the topics discussed in this lecture series.

From playlist Intro to Data Science

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The mother of all representer theorems for inverse problems & machine learning - Michael Unser

This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together leading researchers in the general fields of mathematics, statistics, computer science and engineering. About the event The workshop ai

From playlist Mathematics of data: Structured representations for sensing, approximation and learning

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Machine Learning

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

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Creating World Class Computer Science at Stanford

The panelists discussed Stanford's Computer Science Department within the historical context of higher education, technological innovations, and the Silicon Valley. They talked about how it grew from the university’s administrative needs and those of science and engineering research.

From playlist Stanford Historical Society

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Expanding the Frontiers of Computer Science Education

by Mehran Sahami, Professor (Teaching) of Computer Science, Associate Chair for Education and Director of Educational Affairs, Computer Science, Robert and Ruth Halperin, University Fellow in Undergraduate Education

From playlist Stanford Computer Science 50th Anniversary

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Summer App Space: Demo Day Keynote Speaker: Professor Coleen Lewis - 8/4/17

Dr. Colleen Lewis is a professor of computer science at Harvey Mudd College who specializes in computer science education. Lewis researches how people learn computer science and how people feel about learning computer science. Her research seeks to identify effective teaching practices for

From playlist Innovation Speaker Series - Summer App Space 2017

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Everything You Need to Know as a Computer Science Student

Get two months of Skillshare Premium for free --- https://bit.ly/forrestknight18 My answers to every computer science question asked by y'all. What's the best/most useful major in computer science? I want to be a software engineer. (0:33) What part time jobs should I get as a computer s

From playlist Computer Science

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Why Study Computer Science? | College Majors | College Degrees | Study Hall

What can you do with a Computer Science major? In Computer Science you can expect to study discrete mathematics, probability and statistics, linear algebra, physics and so much more. Basically, Computer Science is the study of computer systems and how they function. If you want to dig de

From playlist Fast Guides: To Electives and Majors

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The Open Source Computer Science Degree

This is my curated list of free courses from reputable universities like MIT, Stanford, and Princeton that satisfy the same requirements as an undergraduate Computer Science degree, minus general education. Everything is open source online and free. My GitHub Repo --- https://github.com/F

From playlist Computer Science

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Open Source Computer Science Degree

In this video, I will be taking you through the various resources that make up the open-source computer science degree. The OSSU curriculum is a complete education in computer science using online materials. It's not merely for career training or professional development. It's for those wh

From playlist Ethical Hacking & Penetration Testing - Complete Course

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Panel Discussion on Teaching Computational Social Science

This event held on June 22, 2020 was part of the 2020 SICSS Festival. Speakers: Matti Nelimarkka (SICSS-Princeton 17, SICSS-Helsinki 18, SICSS-Istanbul 19, 20), Rochelle Terman (SICSS-Princeton 17), and Jae Yeon Kim (SICSS-Princeton 19, SICSS-Bay Area 20) Moderator: Matthew Salganik (SIC

From playlist All Videos

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An Introduction to Computational Social Science

Professor Matthew Salganik of Princeton University gives an introduction to the interdisciplinary field of computational social science, which employs digital data sources and machine learning to study human behavior. Link to the slides used in this video are here: https://github.com/comps

From playlist SICSS 2020

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What We've Learned from NKS Chapter 12: The Principle of Computational Equivalence [Part 3]

In this episode of "What We've Learned from NKS", Stephen Wolfram is counting down to the 20th anniversary of A New Kind of Science with [another] chapter retrospective. If you'd like to contribute to the discussion in future episodes, you can participate through this YouTube channel or th

From playlist Science and Research Livestreams

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Computer Science Basics: Algorithms

We use computers every day, but how often do we stop and think, “How do they do what they do?” This video series explains some of the core concepts behind computer science. To view the entire playlist, visit https://www.youtube.com/playlist?list=PLpQQipWcxwt-Q9izCl0mm-QZ4seuBdUtr. We hop

From playlist Computer Science Basics

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