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MIT 6.S094 Deep Learning Basics: Introduction and Overview

An introductory lecture for MIT course 6.S094 on the basics of deep learning including a few key ideas, subfields, and the big picture of why neural networks have inspired and energized an entirely new generation of researchers. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations […]
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Computerphile: Deep Learning

Google, Facebook & Amazon all use deep learning methods, but how does it work? Research fellow & Deep Learning expert Brais Martinez explains.
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Tensorflow and deep learning – without a PhD by Martin Görner

Subscribe to Devoxx on YouTube @ https://bit.ly/devoxx-youtube Like Devoxx on Facebook @ https://www.facebook.com/devoxxcom Follow Devoxx on Twitter @ https://twitter.com/devoxx Google has recently open-sourced its framework for machine learning and neural networks called Tensorflow. With this new tool, deep machine learning transitions from an area of research into mainstream software engineering. In this session, we will […]
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#52 – Adversarial Examples Beyond Security (Hadi Salman, MIT)

Performing reliably on unseen or shifting data distributions is a difficult challenge for modern vision systems, even slight corruptions or transformations of images are enough to slash the accuracy of state-of-the-art classifiers. When an adversary is allowed to modify an input image directly, models can be manipulated into predicting anything even when there is no […]
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C4W1L01 Computer Vision

Take the Deep Learning Specialization: http://bit.ly/32V2BBe Check out all our courses: https://www.deeplearning.ai Subscribe to The Batch, our weekly newsletter: https://www.deeplearning.ai/thebatch Follow us: Twitter: https://twitter.com/deeplearningai_ Facebook: https://www.facebook.com/deeplearningHQ/ Linkedin: https://www.linkedin.com/company/deeplearningai Source of this AI Video
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Lecture 3 | Learning, Empirical Risk Minimization, and Optimization

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2019 For more information, please visit: http://deeplearning.cs.cmu.edu/ Contents: • Training a neural network • Perceptron learning rule • Empirical Risk Minimization • Optimization by gradient descent YouTube Source for this AI Video
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01:11:23

The Fastai v1 Deep Learning Framework with Jeremy Howard – TWiML Talk #186

In today’s episode we’ll be taking a break from our Strata Data conference series and presenting a special conversation with Jeremy Howard, founder and researcher at Fast.ai. Fast.ai is a company many of our listeners are quite familiar with due to their popular deep learning course. This episode is being released today in conjunction with […]
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PyTorch Tutorial 05 – Gradient Descent with Autograd and Backpropagation

New Tutorial series about Deep Learning with PyTorch! ⭐ Check out Tabnine, the FREE AI-powered code completion tool I use to help me code faster: https://www.tabnine.com/?utm_source=youtube.com&utm_campaign=PythonEngineer * In this part we will learn how we can use the autograd engine in practice. First we will implement Linear regression from scratch, and then we will learn […]
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01:13:42

Continual Learning in Neural Networks by Pulkit Agarwal

This is a guest lecture by Pulkit Agarwal, a Ph.D. student whose current research is on Superposition of Many Models Into One. Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Spring 2019 Slides: The related paper co-authored by Dr. Pulkit Agarwal can be found here: https://arxiv.org/pdf/1902.05522.pdf For more information, please visit: http://deeplearning.cs.cmu.edu/ Content: […]
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14:05

Is Upwork a Scam for Machine Learning Freelancers? Is It Viable in 2020?

Is Upwork still a viable platform for freelancing? Some say no, but I present a different argument in this video. As part of an overall strategy to generate inbound deep learning consulting leads, Upwork can still be a viable platform moving forward. Learn how to turn deep reinforcement learning papers into code: Deep Q Learning: […]
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21:01

Recitation 0 | (2/5) Foundations of Jupyter Notebook with SageMaker Notebook Instances

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Spring 2020 / Fall 2019 Notebook: http://deeplearning.cs.cmu.edu/document/recitation/recitation0c.tar.gz For more information, please visit: http://deeplearning.cs.cmu.edu/ Contents: • AWS Instance Types and Pricing • SageMaker Notebook Instances • Basics of IPython • Modes in Jupyter Notebook • General Jupyter Shortcuts • Jupyter Edit Mode • Jupyter Command Mode […]
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Completing Andrew Ng's Machine Learning Course on Coursera | 100 Days of Code 12

Last week, I finished the Machine Learning course from Standford University and Andrew Ng on Coursera. I also learned more about GANs and continued my Deep Learning Nanodegree. Links mentioned in the video: DCGANs Paper – https://arxiv.org/pdf/1511.06434.pdf Pix2Pix and #edgestocats – https://affinelayer.com/pixsrv/ How I’m Learning Deep Learning in 2017 – https://medium.com/@MrDBourke/how-im-learning-deep-learning-in-2017-part-1-632f4187ce4c Siraj’s Video on GANs […]
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18:19

C4W2L02 Classic Network

Take the Deep Learning Specialization: http://bit.ly/2VMlo09 Check out all our courses: https://www.deeplearning.ai Subscribe to The Batch, our weekly newsletter: https://www.deeplearning.ai/thebatch Follow us: Twitter: https://twitter.com/deeplearningai_ Facebook: https://www.facebook.com/deeplearningHQ/ Linkedin: https://www.linkedin.com/company/deeplearningai Source of this AI Video
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00:38

My new TensorFlow for Deep Learning course is now on Udemy! #shorts

The new Zero to Mastery TensorFlow for Deep Learning course is now available on Udemy! Sign up here: https://dbourke.link/udemyTFlaunch (to celebrate the launch, there’s a great deal going for the next 5 days) Not a fan of Udemy? You can sign up on the Zero to Mastery Academy: TensorFlow course – https://dbourke.link/ZTMTFcourse ML course (beginner-friendly) […]
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18:36

Open Challenges in Deep Learning Systems | PyTorch Developer Day 2020

While machine learning frameworks like PyTorch are always improving, there are still more than a few challenges left to tackle. In this keynote, West Coast Head of Engineering, Kim Hazelwood, talks about the route towards solving the many open problems at the intersection of AI and systems, several worrisome trends like operator explosion, and the […]
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512
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Exponentially Weighted Averages (C2W2L03)

Take the Deep Learning Specialization: http://bit.ly/38iUGz1 Check out all our courses: https://www.deeplearning.ai Subscribe to The Batch, our weekly newsletter: https://www.deeplearning.ai/thebatch Follow us: Twitter: https://twitter.com/deeplearningai_ Facebook: https://www.facebook.com/deeplearningHQ/ Linkedin: https://www.linkedin.com/company/deeplearningai Source of this AI Video
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Forward Propagation in a Deep Network (C1W4L02)

Take the Deep Learning Specialization: http://bit.ly/38kVjbc Check out all our courses: https://www.deeplearning.ai Subscribe to The Batch, our weekly newsletter: https://www.deeplearning.ai/thebatch Follow us: Twitter: https://twitter.com/deeplearningai_ Facebook: https://www.facebook.com/deeplearningHQ/ Linkedin: https://www.linkedin.com/company/deeplearningai Source of this AI Video
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Lecture 16 | (5/5) Recurrent Neural Networks

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2019 For more information, please visit: http://deeplearning.cs.cmu.edu/ Contents: • Sequence-to-sequence models • Attention models • Examples from speech and language YouTube Source for this AI Video