Neural Lab is a no-cost neural network simulator that designs and trains artificial neural networks for use in many fields such as engineering, business, computer science and technology. It integrates with Microsoft Visual Studio using C (Win32 - Wintempla) to incorporate artificial neural networks into custom applications, research simulations or end user interfaces. It provides a visual environment to design and test artificial neural networks. The latest Neural Lab version is 4.1. The two major versions are version 3.1 and 4.0. (Wikipedia).
Research Methods of Biopsychology
With some information regarding the organization of neurons and neural pathways, we are ready to start getting into some deeper topics. But before we do that, it will be useful to get a general sense of precisely how we learn about the things we will be discussing. The brain is complicated
From playlist Biopsychology
Cell Programming Kit - Elowitz Lab
Researchers at Caltech have developed a kind of biological toolkit of parts that can be assembled to create custom circuits for cells.
From playlist Our Research
Mapping The Brain | Digging Deeper
Should the United States spend billions to completely map the human brain? Will it ever be possible to build an artificial brain - and, if we do, what are the implications for the future? Join Ben and Matt as they talk about some interesting stuff that didn't make it into the Deceptive Bra
From playlist Stuff They Don't Want You To Know, New Episodes!
This lecture gives an overview of neural networks, which play an important role in machine learning today. Book website: http://databookuw.com/ Steve Brunton's website: eigensteve.com
From playlist Intro to Data Science
Everything you need to know about Fermilab
Fermilab is one of the world’s finest laboratories dedicated to studying fundamental questions about nature. In this video, Fermilab’s own Dr. Don Lincoln talks about some of Fermilab’s leading research efforts that will lead the field for the next decade or two. If you want to learn more
From playlist LBNF/DUNE/PIP-II
Testing and Online Experimentation
Join Data Science Dojo and Statsig for a conversation on experimentation and testing. Learn how leading companies like Facebook use experimentation to build better products and accelerate their growth with 10x as much testing. Web experimentation can range from simple projects like design
From playlist A/B Testing & Beyond
What Is Quantum Computing | Quantum Computing Explained | Quantum Computer | #Shorts | Simplilearn
🔥Explore Our Free Courses With Completion Certificate by SkillUp: https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=QuantumComputingShorts&utm_medium=ShortsDescription&utm_source=youtube Quantum computing is a branch of computing that focuses on developing computer tech
From playlist #Shorts | #Simplilearn
MATH1031 Users of Mathematics - Neuroscience
Math1031 Users of Mathematics Neuroscience
From playlist MATH1031 Mathematics For Life Sciences
NVIDIA Deep Learning Course Class #1 – Introduction to Deep Learning
Register for the full course at https://developer.nvidia.com/deep-learning-courses This first in a series of webinars Introduction to Deep Learning covers basics of Deep Learning, why it excels when running on GPUs, and the three major frameworks available for taking advantage of Deep Lear
From playlist Deep Neural Networks
History of Science and Technology Q&A (Mar. 10, 2021)
Stephen Wolfram hosts a live and unscripted Ask Me Anything about the history of science and technology for all ages. Originally livestreamed at: https://twitch.tv/stephen_wolfram/ Outline of Q&A 0:00 Stream starts 3:17 Stephen begins the stream 3:46 When did Neural Networks (and more ge
From playlist Stephen Wolfram Ask Me Anything About Science & Technology
NVIDIA Deep Learning Course: Class #5 - Getting started with Torch7
Register for the full course and find the Q&A log at https://developer.nvidia.com/deep-learning-courses Torch is a scientific computing framework. It uses an easy and fast scripting language called Lua, but accesses a very fast underlying C/CUDA implementation with transparent GPU integra
From playlist Deep Neural Networks
MIT Introduction to Deep Learning | 6.S191
MIT Introduction to Deep Learning 6.S191: Lecture 1 *New 2022 Edition* Foundations of Deep Learning Lecturer: Alexander Amini For all lectures, slides, and lab materials: http://introtodeeplearning.com/ Lecture Outline 0:00 - Introduction 6:35 - Course information 9:51 - Why deep lea
From playlist Introduction to Deep Learning
The Epistemology of Deep Learning - Yann LeCun
Deep Learning: Alchemy or Science? Topic: The Epistemology of Deep Learning Speaker: Yann LeCun Affiliation: Facebook AI Research/New York University Date: February 22, 2019 For more video please visit http://video.ias.edu
From playlist Mathematics
Casey Greene: "Deep learning: privacy preserving data sharing along with some hints and tips"
Computational Genomics Winter Institute 2018 "Deep learning: privacy preserving data sharing along with some hints and tips" Casey Greene, University of Pennsylvania Perelman School of Medicine Institute for Pure and Applied Mathematics, UCLA March 2, 2018 For more information: http://c
From playlist Computational Genomics Winter Institute 2018
Luca Mazzucato - Computational Principles Underlying the Temporal Organization of Behavior
Naturalistic animal behavior exhibits a striking amount of variability in the temporal domain along at least three independent axes: hierarchical, contextual, and stochastic. First, a vast hierarchy of timescales links movements into behavioral sequences and long-term activities, from mill
From playlist Mikefest: A conference in honor of Michael Douglas' 60th birthday
Neural Network Architectures & Deep Learning
This video describes the variety of neural network architectures available to solve various problems in science ad engineering. Examples include convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders. Book website: http://databookuw.com/ Steve Brunton
From playlist Data Science
Regulation of Aging - Anne Brunet
Anne Brunet, Professor of Genetics at Stanford University, is interested in understanding agin based on the integration of model organisms with diverse lifespans.
From playlist Wu Tsai Neurosciences Institute
MIT 6.S191: Recurrent Neural Networks and Transformers
MIT Introduction to Deep Learning 6.S191: Lecture 2 Recurrent Neural Networks Lecturer: Ava Soleimany January 2022 For all lectures, slides, and lab materials: http://introtodeeplearning.com Lecture Outline 0:00 - Introduction 1:59 - Sequence modeling 4:16 - Neurons with recurrence 10
From playlist Introduction to Machine Learning
Joe Lykken, Fermilab's deputy director of research, discusses the future of quantum computing and science - including the role organizations like Fermilab will play. Learn more about the Fermilab Quantum Institute at https://quantum.fnal.gov/ For more information on Fermilab, visit https:
From playlist Quantum Physics
NVIDIA Deep Learning Course: Class #3 - Getting started with Caffe
Register for the full course and find the Q&A log at https://developer.nvidia.com/deep-learning-courses Caffe is a Deep Learning framework developed by the Berkeley Vision and Learning Center (BVLC) and by a large community of open-source contributors. Caffe allows the user to define, tr
From playlist Deep Neural Networks