NOTE: The first video of the ML Foundations Course is coming from the 6 session of the AI Foundations Course This video was recorded on July 14, 2020 Slides from the presentation are available here: https://www.h2o.ai/community/viewdocument/ai-foundations-v1-072120-module-3?CommunityKey=6086b4fe-7ee8-4a71-bceb-12e00d5db450&tab=librarydocuments To find additional videos on ML courses, earn badges, join the courses at H2O.ai Learning Center: https://training.h2o.ai/products/ai-foundations-course OUTLINE: 0:00 – AI Foundations 3:14 – Why we are Here 5:10 – Determine Need & Use Cases for AI 25:09 – Design & Evaluate Model Architectures 39:10 – Assess Key Use Cases 46:14 – Finalize your AI Proposal 50:31 – What’s Next? 51:36 – Resources Description: Machine learning is one of the most active areas of artificial intelligence, powered by data. In this module, you will learn the essential building blocks of machine learning through the use of case studies. You will be introduced to the data science workflow and frameworks to help you turn business problems into machine learning problems. By the end of this module, you will be able to apply machine learning methods to a wide variety of domains and applications. One of the most critical aspects of a successful AI implementation is having a clear approach that ensures all key stakeholders understand the relevant aspects of the proposed solution. In this session, you will learn how to identify appropriate AI use cases, evaluate architecture-readiness, and complete an AI proposal that will set the stage for a successful AI business solution. Speaker: Parul Pandey (H2O.ai – Data Science Evangelist)
The talks at the Deep Learning School on September 24/25, 2016 were amazing. I clipped out individual talks from the full live streams and provided links to each below in case that’s useful for people who want to watch specific talks several times (like I do). Please check out the official website (http://www.bayareadlschool.org) and full live streams below. Having read, watched, and presented deep learning material over the past few years, I have to say that this is one of the best collection of introductory deep learning talks I’ve yet encountered. Here are links to the individual talks and the full live streams for the two days: 1. Foundations of Deep Learning (Hugo Larochelle, Twitter) – https://youtu.be/zij_FTbJHsk 2. Deep Learning for Computer Vision (Andrej Karpathy, OpenAI) – https://youtu.be/u6aEYuemt0M 3. Deep Learning for Natural Language Processing (Richard Socher, Salesforce) – https://youtu.be/oGk1v1jQITw 4. TensorFlow Tutorial (Sherry Moore, Google Brain) – https://youtu.be/Ejec3ID_h0w 5. Foundations of Unsupervised Deep Learning (Ruslan Salakhutdinov, CMU) – https://youtu.be/rK6bchqeaN8 6. Nuts and Bolts of Applying Deep Learning (Andrew Ng) – https://youtu.be/F1ka6a13S9I 7. Deep Reinforcement Learning (John Schulman, OpenAI) – https://youtu.be/PtAIh9KSnjo 8. Theano Tutorial (Pascal Lamblin, MILA) – https://youtu.be/OU8I1oJ9HhI 9. Deep Learning for Speech Recognition (Adam Coates, Baidu) – https://youtu.be/g-sndkf7mCs 10. Torch Tutorial (Alex Wiltschko, Twitter) – https://youtu.be/L1sHcj3qDNc 11. Sequence to Sequence Deep Learning (Quoc Le, Google) – https://youtu.be/G5RY_SUJih4 12. Foundations and Challenges of Deep Learning (Yoshua Bengio) – https://youtu.be/11rsu_WwZTc Full Day Live Streams: Day 1: https://youtu.be/eyovmAtoUx0 Day 2: https://youtu.be/9dXiAecyJrY Go to http://www.bayareadlschool.org for more information on the event, speaker [More]
Over the past several centuries, the human condition has been profoundly changed by the agricultural and industrial revolutions. With the creation and continued development of AI, we stand in the midst of an ongoing intelligence revolution that may prove far more transformative than the previous two. How did we get here, and what were the intellectual foundations necessary for the creation of AI? What benefits might we realize from aligned AI systems, and what are the risks and potential pitfalls along the way? In the longer term, will superintelligent AI systems pose an existential risk to humanity? Steven Pinker, best selling author and Professor of Psychology at Harvard, and Stuart Russell, UC Berkeley Professor of Computer Science, join us on this episode of the AI Alignment Podcast to discuss these questions and more. Topics discussed in this episode include: -The historical and intellectual foundations of AI -How AI systems achieve or do not achieve intelligence in the same way as the human mind -The rise of AI and what it signifies -The benefits and risks of AI in both the short and long term -Whether superintelligent AI will pose an existential risk to humanity You can find the page for this podcast here: https://futureoflife.org/2020/06/15/steven-pinker-and-stuart-russell-on-the-foundations-benefits-and-possible-existential-risk-of-ai/ You can take a survey about the podcast here: https://www.surveymonkey.com/r/W8YLYD3 You can submit a nominee for the Future of Life Award here: https://futureoflife.org/future-of-life-award-unsung-hero-search/ Timestamps: 0:00 Intro 4:30 The historical and intellectual foundations of AI 11:11 Moving beyond dualism 13:16 Regarding the objectives of an agent as [More]
Godfather of artificial intelligence Geoffrey Hinton gives an overview of the foundations of deep learning. In this talk, Hinton breaks down the advances of neural networks, as applied to speech and object recognition, image segmentation and reading or generating natural written language. For more info visit: Website: http://elevatetechfest.com Twitter: @elevatetechfest Facebook: @elevatetechfest Instagram: @elevatetechfest