Artificial neural networks | Neural network software
Neural network software is used to simulate, research, develop, and apply artificial neural networks, software concepts adapted from biological neural networks, and in some cases, a wider array of adaptive systems such as artificial intelligence and machine learning. (Wikipedia).
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
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
In this video, I present some applications of artificial neural networks and describe how such networks are typically structured. My hope is to create another video (soon) in which I describe how neural networks are actually trained from data.
From playlist Machine Learning
What is Neural Network in Machine Learning | Neural Network Explained | Neural Network | Simplilearn
This video by Simplilearn is based on Neural Networks in Machine Learning. This Neural Network in Machine Learning Tutorial will cover the fundamentals of Neural Networks along with theoretical and practical demonstrations for a better learning experience 🔥Enroll for Free Machine Learning
From playlist Machine Learning Algorithms [2022 Updated]
This lecture discusses some key limitations of neural networks and suggests avenues of ongoing development. Book website: http://databookuw.com/ Steve Brunton's website: eigensteve.com
From playlist Intro to Data Science
Deep Learning with Neural Networks and TensorFlow Introduction
Welcome to a new section in our Machine Learning Tutorial series: Deep Learning with Neural Networks and TensorFlow. The artificial neural network is a biologically-inspired methodology to conduct machine learning, intended to mimic your brain (a biological neural network). The Artificial
From playlist Machine Learning with Python
Neural Network Architectures | Types of Neural Network Architectures | Neural Network | Simplilearn
This video by simplilearn is based on artificial neural network architecture. This artificial intelligence and machine learning tutorial will help you understand neural network architectures in detail and types of neural network architectures. this neural network tutorial will include both
From playlist Machine Learning Algorithms [2022 Updated]
Neural Networks 1 Neural Units
From playlist Week 5: Neural Networks
The Hardware Lottery (Paper Explained)
#ai #research #hardware We like to think that ideas in research succeed because of their merit, but this story is likely incomplete. The term "hardware lottery" describes the fact that certain algorithmic ideas are successful because they happen to be suited well to the prevalent hardware
From playlist Papers Explained
The Computer Chronicles - Neural Networks (1991)
Special thanks to archive.org for hosting these episodes. Downloads of all these episodes and more can be found at: http://archive.org/details/computerchronicles
From playlist The Computer Chronicles 1991 Episodes
Safety and robustness for deep learning with provable guarantees - Marta Kwiatkowska - Oxford
Computing systems are becoming ever more complex, with automated decisions increasingly often based on deep learning components. A wide variety of applications are being developed, many of them safety-critical, such as self-driving cars and medical diagnosis. Since deep learning is unstabl
From playlist Interpretability, safety, and security in AI
Will Tesla’s AI Become Dangerous?
Recently Tesla demonstrated their Tesla Humanoid Robot as part of the “Tesla AI Day”. To be honest the demonstration itself wasn’t all that impressive, we have seen more astonishing things before - robots doing parkour and Disney’s Robot Spiderman spring to mind. Tesla’s robot, called Opti
From playlist Case Studies
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
Deep Learning and Deep Integration via Jupyter - Douglas Blank
Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi Follow O'Reilly on: Twitter: http://twitter.com/oreillymedia Facebook: http://facebook.com/OReilly Instagram: https://www.instagram.com/oreillymedia LinkedIn: https://www.linkedin.com/company-beta/8459/
From playlist The O’Reilly Jupyter Pop-up
Full Self-Driving is HARD! Analyzing Elon Musk re: Tesla Autopilot on Lex Fridman's Podcast
#tesla #fsd #elon Watch the original podcast: https://www.youtube.com/watch?v=DxREm3s1scA An analysis of Elon's appearance on Lex Fridman. Very interesting conversation and a good overview of past, current, and future versions of Tesla's Autopilot system. OUTLINE: 0:00 - Intro 0:40 - Te
From playlist Talk Analysis
Stanford Seminar - Challenges in AI Safety: A Perspective from an Autonomous Driving Company
April 6, 2022 Jerry Lopez of Motional There is a long legacy of deploying complex software in safety critical applications in industries like aviation and automotive. The increasing use of Machine Learning (ML) models in these applications has forced the engineering community to rethink w
From playlist Stanford CS521 - AI Safety Seminar
Neural Networks and Deep Learning
This lecture explores the recent explosion of interest in neural networks and deep learning in the context of 1) vast and increasing data sets, and 2) rapidly improving computational hardware, which have enabled the training of deep neural networks. Book website: http://databookuw.com/
From playlist Intro to Data Science
Neural Network Fundamentals (Part1): Input and Output
I have a more up to date, clearer, and faster :-) version here: https://www.youtube.com/watch?v=fAfr48Fh2eI From http://www.heatonresearch.com. A simple introduction to how to represent the XOR operator to machine learning structures, such as a neural network or support vector machine.
From playlist Neural Networks by Jeff Heaton
Dataset for Deep Learning - Fashion MNIST
This series is all about neural network programming and artificial intelligence. In this post, we will look closely at the importance of data in deep learning by exploring cutting edge concepts in software development, and taking a deep dive into a relatively new dataset. References: Urs
From playlist PyTorch - Python Deep Learning Neural Network API
