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This is a Machine Learning & Data Science Tutorial series for Beginners to Advance with Python Free reference books – Python Data Science Handbook: https://tanthiamhuat.files.wordpress.com/2018/04/pythondatasciencehandbook.pdf R For Data Science: https://r4ds.had.co.nz/index.html Rules For Machine Learning: http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf Deep Learning: https://www.deeplearningbook.org/
Enroll for free in the below link to get all the videos and materials https://courses.ineuron.ai/Deep-Learning-Community-Class Live Deep Learning Playlist: https://www.youtube.com/watch?v=8arGWdq_KL0&list=PLZoTAELRMXVPiyueAqA_eQnsycC_DSBns Our Popular courses:- Fullstack data science job guaranteed program:- bit.ly/3JronjT Tech Neuron OTT platform for Education:- bit.ly/3KsS3ye Affiliate Portal (Refer & Earn):- https://affiliate.ineuron.ai/ Internship Portal:- https://internship.ineuron.ai/ Website:- www.ineuron.ai iNeuron Youtube Channel:- https://www.youtube.com/channel/UCb1GdqUqArXMQ3RS86lqqOw Telegram link: https://t.me/joinchat/N77M7xRvYUd403DgfE4TWw Please do subscribe my other channel too https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06
The Center for Research on Foundation Models (CRFM), a new initiative of the Stanford Institute for Human-Centered Artificial Intelligence (HAI), hosted the Workshop on Foundation Models from August 23-24, 2021. The workshop convened experts and scholars reflecting a diverse array of perspectives and backgrounds to discuss opportunities, challenges, limitations, and societal impact of these emerging technologies. Speakers in this session: Introduction Fei-Fei Li, Sequoia Professor, Computer Science Department, Stanford University; Denning Co-Director, Stanford Institute for Human-Centered Artificial Intelligence Foundation Models Percy Liang, Associate Professor of Computer Science, Stanford University
(Introductions by Professor Rob Reich, President Marc Tessier-Lavigne, and grad student Margaret Guo end at 13:52.) Twin revolutions at the start of the 21st century are shaking up the very idea of what it means to be human. Computer vision and image recognition are at the heart of the AI revolution. And CRISPR is a powerful new technique for genetic editing that allows humans to intervene in evolution. Jennifer Doudna and Fei-Fei Li, pioneering scientists in the fields of gene editing and artificial intelligence, respectively, discuss the ethics of scientific discovery. Russ Altman moderated the conversation.
Stanford was one of the pioneers in artificial intelligence. Hear from professors such as Chris Manning and Fei-Fei Li on the earliest days of natural language processing and computer vision, the work of scholars John McCarthy and Jay McClelland, the launch of the Stanford AI Lab, early robotics at the school, and other pivotal moments in Stanford AI.
Moderated by Eric Horvitz, Managing Director, Microsoft Research Panelists: Fei-Fei Li, Associate Professor, Stanford University Michael Littman, Professor of Computer Science, Brown University Josh Tenenbaum, Professor, Massachusetts Institute of Technology Oren Etzioni, Chief Executive Officer, Allen Institute for Artificial Intelligence Christopher Bishop, Distinguished Scientist, Microsoft Research
The biggest invention of humankind : AI So what is today’s point ? Do AI will shake hands with us and will wrote a new generation of humankind. OR Will changed as a Foe as soon as they get smarter. Is there something going on in their programs? Check the video #ai #artificialintelligence #robots #futurewithai
Speaker : Dr. Harsh Mahajan Chair Persons : Dr. Chand Wattal & Dr. J Jayalakshmi  Moderator : Dr. Alok Ahuja
CactusCon 10 (2022) Talk CC10 – Artificial Intelligence: Friend or Foe in the Context of Ransomware Aaron Rose Live Q&A For this talk: https://youtu.be/8jgkZDlY7SY Join us on Discord! https://cactuscon.com/cc10 The industrial revolution was powered by coal and steam. They were the power that enabled innovation and propelled the world down the road that has brought us to where we are today. The next revolution is on the horizon, and it’s an information revolution. Smartphones, smart homes, and smart assistants are proliferating our lives. Artificial intelligence is becoming in integral contributor to how this technology adds value to the our lives. The capabilities of the cyber security ecosystem must keep pace with this evolution. During this session we will cover how artificial intelligence is being used to fuel the next generation of cyber security ecosystems. We will see how it can be used to improve accuracy, speed and efficiency of enforcement technologies while enhancing the information used to make business and security decisions. On the other hand, how could AI & Machine Learning be used against us? If we have the technology, so do our adversaries. Aaron Rose is a Cyber Security Evangelist, Security Architect & Member of the Office of the CTO at Check Point Software Technologies. A subject matter expert in Cloud, Internet of Things, and Application security; Aaron has focused his career on securing organizations & their resources beyond the perimeter of the traditional network firewall. An avid international traveler, Aaron welcomed the opportunity to spend three months [More]
Artificial Intelligence (or AI for short) is becoming increasingly more common in everyday life, affecting every aspect of how we live. Ever wondered how your social media feeds are showing up with the items you just researched? Companies are increasingly turning to AI to help them understand their customers better and plan for the future. But is it making the world a better place, or are we going to be replaced by computers? In this virtual event we’re going to be looking at where do we draw the line? How we manage the fear? Is regulation the answer? And are you happy with decisions being made for you and ultimately, is AI a friend… or a foe? We’re delighted to be joined at this event by Dennis Dokter and Nik Lomax. Dennis is the Relationship Officer at Nexus, the University of Leeds’ innovation hub. With a strong background in Philosophy and Ethics of Society Science & Technology, Dennis’ specialties are dealing with questions on data and research methodology. Nik Lomax is Associate Professor of Data Analytics for Population Research at the University of Leeds. He is a Fellow at the Alan Turing Institute for Data Science and Artificial Intelligence and is co-Director of the Economic and Social Research Council funded Consumer Data Research Centre.
Learn English with the legend Elon Musk in this enlightened Speech. In this conversation Elon Must talks about our Future, Artificial Intelligence (A.I) and Mars at World Government Summit moderated by H.E. Mohammad AlGergawi – Watch with big English subtitles. ✅ Get the full transcript and audio of this speech FREE on our website: https://www.englishspeecheschannel.com/english-speeches/elon-musk-speech ✅ Also, download our FREE English Ebooks: https://www.englishspeecheschannel.com/ebook/free-english-ebook ✅ Do you want to become a better writer, reader, speaker, and speller? Check our NEW eBook: https://www.englishspeecheschannel.com/perfect-grammar-ebook 👉 How to Learn English Online and from Home: https://www.englishspeecheschannel.com/english-tips/how-to-learn-english-online Follow us on Social Media: 👉 Instagram: englishspeeches 👉 Facebook: englishspeeches 👉 Twitter: englishspeeches All content on our website is totally FREE. The only thing we ask is: Please! SUBSCRIBE to our Channel: 🙏🏻 https://www.youtube.com/englishspeeches?sub_confirmation=1 ❤️ Thank you for watching! #EnglishSpeeches #EnglishSubtitles #LearnEnglish #EnglishSpeech #ElonMuskSpeech Link to the original video: https://youtu.be/rCoFKUJ_8Yo We use this video for educational purposes. Thank you for making this Speech possible. FAIR-USE COPYRIGHT DISCLAIMER * Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, commenting, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. 1)This video has no negative impact on the original works (It would actually be positive for them) 2)This video is also for teaching purposes. 3)It is not transformative in nature. 4)I only used bits and [More]
I’m going to show you how AI is going to change the world and what we need to think about. Predictions and questions about artificial intelligence
Lex Fridman Podcast full episode: https://www.youtube.com/watch?v=aGBLRlLe7X8 Please support this podcast by checking out our sponsors: – Shopify: https://shopify.com/lex to get 14-day free trial – Weights & Biases: https://lexfridman.com/wnb – Magic Spoon: https://magicspoon.com/lex and use code LEX to get $5 off – Blinkist: https://blinkist.com/lex and use code LEX to get 25% off premium GUEST BIO: Oriol Vinyals is the Research Director and Deep Learning Lead at DeepMind. PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 SOCIAL: – Twitter: https://twitter.com/lexfridman – LinkedIn: https://www.linkedin.com/in/lexfridman – Facebook: https://www.facebook.com/lexfridman – Instagram: https://www.instagram.com/lexfridman – Medium: https://medium.com/@lexfridman – Reddit: https://reddit.com/r/lexfridman – Support on Patreon: https://www.patreon.com/lexfridman
Lex Fridman Podcast full episode: https://www.youtube.com/watch?v=aGBLRlLe7X8 Please support this podcast by checking out our sponsors: – Shopify: https://shopify.com/lex to get 14-day free trial – Weights & Biases: https://lexfridman.com/wnb – Magic Spoon: https://magicspoon.com/lex and use code LEX to get $5 off – Blinkist: https://blinkist.com/lex and use code LEX to get 25% off premium GUEST BIO: Oriol Vinyals is the Research Director and Deep Learning Lead at DeepMind. PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 SOCIAL: – Twitter: https://twitter.com/lexfridman – LinkedIn: https://www.linkedin.com/in/lexfridman – Facebook: https://www.facebook.com/lexfridman – Instagram: https://www.instagram.com/lexfridman – Medium: https://medium.com/@lexfridman – Reddit: https://reddit.com/r/lexfridman – Support on Patreon: https://www.patreon.com/lexfridman
Oriol Vinyals is the Research Director and Deep Learning Lead at DeepMind. Please support this podcast by checking out our sponsors: – Shopify: https://shopify.com/lex to get 14-day free trial – Weights & Biases: https://lexfridman.com/wnb – Magic Spoon: https://magicspoon.com/lex and use code LEX to get $5 off – Blinkist: https://blinkist.com/lex and use code LEX to get 25% off premium EPISODE LINKS: Oriol’s Twitter: https://twitter.com/oriolvinyalsml Oriol’s publications: https://scholar.google.com/citations?user=NkzyCvUAAAAJ DeepMind’s Twitter: https://twitter.com/DeepMind DeepMind’s Instagram: https://instagram.com/deepmind DeepMind’s Website: https://deepmind.com Papers: 1. Gato: https://deepmind.com/publications/a-generalist-agent 2. Flamingo: https://deepmind.com/blog/tackling-multiple-tasks-with-a-single-visual-language-model 3. Language Models are Few-Shot Learners: https://arxiv.org/abs/2005.14165 4. Emergent Abilities of Large Language Models: https://arxiv.org/abs/2206.07682 5. Attention Is All You Need: https://proceedings.neurips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 OUTLINE: 0:00 – Introduction 0:34 – AI 15:31 – Weights 21:50 – Gato 56:38 – Meta learning 1:10:37 – Neural networks 1:33:02 – Emergence 1:39:47 – AI sentience 2:03:43 – AGI SOCIAL: – Twitter: https://twitter.com/lexfridman – LinkedIn: https://www.linkedin.com/in/lexfridman – Facebook: https://www.facebook.com/lexfridman – Instagram: https://www.instagram.com/lexfridman – Medium: https://medium.com/@lexfridman – Reddit: https://reddit.com/r/lexfridman – Support on Patreon: https://www.patreon.com/lexfridman
Abstract: Probabilistic numerics provides a narrative to extend our traditional approach of uncertainty about data to uncertainty about computations. In this talk I will provide a brief background to Probabilistic numerics and show why it is beneficial to think about Bayesian optimisation and other active learning techniques within this framework. In specific I will show how these guiding principles have allowed us to formulate a set of surrogate models that allows us to focus on details that are informative for search while ignoring detrimental structures that are challenging to model from few observations. We will show how this leads to a significantly more robust and efficient active learning loop. Preprints: The talk is primarily based on Bodin, E., Kaiser, M., Kazlauskaite, I., Dai, Z., Campbell, N. D. F., & Ek, C. H., Modulating surrogates for bayesian optimization., In , Proceedings of the 37th International Conference on Machine Learning, {ICML} 2019, 12-18 July 2020, Virtual (pp. ) (2020). Speaker: Dr. Carl Henrik Ek is a senior lecturer at the University of Cambridge. Together with Prof. Neil Lawrence, Jessica Montgomery and Dr. Ferenc Huzar he leads the newly formed machine learning research group in the Cambridge computer lab. He is interested in building models that allows for principled treatment of uncertainty that provides interpretable handles to introduce strong prior knowledge. Personal website can be found at http://carlhenrik.com/. This talk was given at Secondmind Labs, as a part of our (virtual) research seminar. Our research seminar is where we exchange ideas with guest [More]
As smart conversational interfaces are seeing more use in IT, sales, and marketing, tapping the power of chatbot automation that you already own is a good thing. Join us and learn from an expert, ask a question, or hear from your peers on how you can successfully activate and automate your IT Service Management with ServiceNow Virtual Agent — the end-to-end, intelligent conversational experience that enables instant resolution to common requests, increases employee and customer satisfaction, and keep agents focused on more pressing issues. Walk away from this session with tips and tricks to prepare your implementation resources, determine governance, and identify top uses and business outcomes to automate ServiceNow Virtual Agent.
Check out Avaamo’s Conversational AI platform for Wealth management using which you can ask you intelligent risk assessment questions, suggest portfolio changes based on your goals, and help you track portfolio performance . Learn more about Avaamo’s AI powered offerings for financial services by visiting : http://www.avaamo.ai/banking-services/
The Naked Dialogue Podcast EP#25: Joscha Bach, Sanjana Singh & Abraham Munoz Bravo | The Logic of the Universe, Computational Mind & The Limits of the Unknown Spotify: https://open.spotify.com/show/36PhC0Xl4W9neFHc58agFH Apple Podcasts: https://podcasts.apple.com/us/podcast/the-naked-dialogue-podcast/id1541757228 Anchor.fm: https://anchor.fm/sanjanasinghx/support YouTube: https://www.youtube.com/channel/UCm7q8BXAjjitSG9sXAv-T8A https://linktr.ee/TheNakedDialogue CONTACT: thenakedialguepodcast@gmail.com Joscha Bach: http://bach.ai/ Joscha Bach is a cognitive scientist focusing on cognitive architectures, models of mental representation, emotion, motivation, and sociality. Sanjana Singh (The Host): https://itsa2amgrunge.com/ https://linktr.ee/sanjanasingh CONTACT: sanjanaaaax@gmail.com Abraham Munoz Bravo: https://www.abrahammunozbravo.com/ https://abraham-mb.medium.com/
Ethics & Society: The future of AI: Views from history We hear from Dr Richard Staley, Dr Sarah Dillon, and Dr Jonnie Penn, co-organisers of an Andrew W. Mellon Foundation Sawyer Seminar on the ‘Histories of Artificial Intelligence.’ They share their insights from a year-long study undertaken with a range of international participants on what the histories of AI reveal about power, automation narratives, and how we model and understand climate change. Dr. Sarah Dillon, Reader in Literature and the Public Humanities, University of Cambridge Dr. Richard Staley, Reader in History and Philosophy of Science, University of Cambridge Dr. Jonnie Penn, Researcher at Berkman Klein Center for Internet & Society at Harvard University on LinkedIn #CogX2021 #JoinTheConversation
For full forum click here: https://youtu.be/ucic8cuEd6A INSTAGRAM: https://www.instagram.com/veritasforum FACEBOOK: https://www.facebook.com/veritasforum SUBSCRIBE: https://www.youtube.com/subscription_center?add_user=VeritasForum Find this and many other talks at http://www.veritas.org/engage Over the past two decades, The Veritas Forum has been hosting vibrant discussions on life’s hardest questions and engaging the world’s leading colleges and universities with Christian perspectives and the relevance of Jesus. Learn more at http://www.veritas.org, with upcoming events and over 600 pieces of media on topics including science, philosophy, music, business, medicine, and more!
How seriously is the data science industry taking the issue of bias in machine learning? In this clip taken from a recent CareerFoundry live event senior Data Scientist Tom Gadsby will share some thoughts on the matter! Want more content like this? Check out CareerFoundry’s events page for more deep dive data based content, and much more: https://careerfoundry.com/en/events/ — Looking to start a career in Data? Take your first steps with CareerFoundry’s free data analytics short course: https://bit.ly/CareerFoundryFreeDataAnalyticsShortCourse_023 Want a deeper dive on some key UX topics? Check out CareerFoundry’s blog here: https://careerfoundry.com/en/blog/ Thanks for watching! #DataAnalytics #DataScience #Shorts Want more from CareerFoundry? Check out our other social media channels and blog here: 🔍 https://linktr.ee/CareerFoundry​ For more information on our programs, visit us at: 🖥 https://careerfoundry.com/ Data Science – Bias In Machine Learning Algorithms https://youtu.be/oIEFa1XuDJk
Extensive evidence has shown that AI can embed human and societal bias and deploy them at scale. And many algorithms are now being reexamined due to illegal bias. So how do you remove bias & discrimination in the machine learning pipeline? In this webinar you’ll learn the debiasing techniques that can be implemented by using the open source toolkit AI Fairness 360. AI Fairness 360 (AIF360, https://aif360.mybluemix.net/) is an extensible, open source toolkit for measuring, understanding, and removing AI bias. AIF360 is the first solution that brings together the most widely used bias metrics, bias mitigation algorithms, and metric explainers from the top AI fairness researchers across industry & academia. Trisha Mahoney is an AI Tech Evangelist for IBM with a focus on Fairness & Bias. Trisha has spent the last 10 years working on Artificial Intelligence and Cloud solutions at several Bay Area tech firms including (Salesforce, IBM, Cisco). Prior to that, Trisha spent 8 years working as a data scientist in the chemical detection space. She holds an Electrical Engineering degree and an MBA in Technology Management. https://aif360.mybluemix.net/ https://aif360.slack.com/ http://ibm.biz/Bdqbd2
Authors: Yan Huang; Param Vir Singh, Runshan Fu, Carnegie Mellon University Artificial intelligence (AI) and machine learning (ML) algorithms are widely used throughout our economy in making decisions that have far-reaching impacts on employment, education, access to credit, and other areas. Initially considered neutral and fair, ML algorithms have recently been found increasingly biased, creating and perpetuating structural inequalities in society. With the rising concerns about algorithmic bias, a growing body of literature attempts to understand and resolve the issue of algorithmic bias. In this tutorial, we discuss five important aspects of algorithmic bias. We start with its definition and the notions of fairness policy makers, practitioners, and academic researchers have used and proposed. Next, we note the challenges in identifying and detecting algorithmic bias given the observed decision outcome, and we describe methods for bias detection. We then explain the potential sources of algorithmic bias and review several bias-correction methods. Finally, we discuss how agents’ strategic behavior may lead to biased societal outcomes, even when the algorithm itself is unbiased. We conclude by discussing open questions and future research directions.
#datascience #aiethics #techforgood Increasingly, data and technologies such as artificial intelligence (AI) and machine learning are involved with everyday decisions in business and society. From tools that sort our online content feeds to online image moderation systems and healthcare, algorithms power our daily lives. But with new technologies come questions about how these systems can be used for good – and it is up to data scientists, software engineers and entrepreneurs to tackle these questions. To learn about issues such as ethical AI and using technology for good, we speak with Rayid Ghani, professor in the Machine Learning Department of the School of Computer Science at Carnegie Mellon University and former Chief Scientist at Obama for America 2012. Professor Ghani has an extraordinary background at the intersection of data science and ethics, making this an exciting and unique show! — The conversation includes these important topics: — About Rayid Ghani and technology for good — Why is responsible AI important? — What are the ethical challenges in data science and AI? — What is the source of bias in AI? — What are some examples of AI ethical issues in healthcare? — What is the impact of culture in driving socially responsible AI? — How can we address human bias when it comes to AI and machine learning? — How can we avoid human bias in AI algorithms and data? — What skills are needed to create explainable AI and focus on AI ethics and society? — What kinds of [More]