Talks with Prof. Hugo Aerts, Prof. Hayit Greenspan, Prof. Haotian Lin, Prof. Kang Zhang and Prof. Baiying Lei, chaired by Dr Elena Bellafante, Senior Scientific Editor, Med Recorded at the BMSTC-Cell Press joint conference “The future of medicine: development and applications of AI in disease biology and health care”. Video starts at 00:00 Prof. Hugo Aerts (starts at 00:03) Topic: Artificial intelligence for cancer imaging Prof. Hayit Greenspan (starts at 27:43) Topic: AI in medical imaging for clinical decision making Prof. Haotian Lin (starts at 55:19) Topic: Artificial intelligence in ophthalmology: A window into systemic diseases Prof. Kang Zhang (starts at 01:08:43) Topic: Clinical diagnosis and outcome predictions enabled by big data and AI Prof. Baiying Lei (starts at 01:41:49) Topic: Multi-time multi-modal neuroimage learning for brain disease diagnosis
This session from the NVIDIA AI Tech Workshop led by Director of AI Infrastructure, Joshua Patterson. He presents the origins of RAPIDS and how it aims to accelerate the entire data science pipeline including data loading, ETL, model training, and inference for more productive, interactive, and exploratory workflows. Presentation slides will be uploaded soon for reference.
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
Speaker : Dr. Harsh Mahajan Chair Persons : Dr. Chand Wattal & Dr. J Jayalakshmi  Moderator : Dr. Alok Ahuja
Max Tegmark – Professor, MIT The Applied Machine Learning Days channel features talks and performances from the Applied Machine Learning Days. AMLD is one of the largest machine learning & AI events in Europe, focused specifically on the applications of machine learning and AI, making it particularly interesting to industry and academia. Follow AMLD: on Twitter: https://www.twitter.com/appliedmldays on LinkedIn: https://www.linkedin.com/company/appliedmldays AMLD Website: https://www.appliedmldays.org
For downloading the AI Tool go to : www.eduvance.in/downloads For downloading the datasets go to : www.tinyurl.com/ai-course-datasets http://www.eduvance.in http://www.facebook.com/Eduvance http://www.instagram.com/eduvance #eduvance, #artificialintelligence, #machinelearning, #robot, #images, #image classification, #visualrecognition, #dataset, data, #course, #student #training, #online course, #elearning, #aisoftware, #prediction, #mimodel, #aimodel, #features, #output, #classification, #regression, #gui mode, #programming mode, #python, #python programming, #algorithm, #confusion #matrix, #mse, #r2
For downloading the AI Tool go to : www.eduvance.in/downloads For downloading the datasets go to : www.tinyurl.com/ai-course-datasets http://www.eduvance.in http://www.facebook.com/Eduvance http://www.instagram.com/eduvance #eduvance, #artificialintelligence, #machinelearning, #robot, #images, #image classification, #visualrecognition, #dataset, data, #course, #student #training, #online course, #elearning, #aisoftware, #prediction, #mimodel, #aimodel, #features, #output, #classification, #regression, #gui mode, #programming mode, #python, #python programming, #algorithm, #confusion #matrix, #mse, #r2
The AI Crash Course The AI Crash Course is an opportunity to learn from experts in the field about the applications of AI, its risks, challenges and opportunities. The course is open for a global community to understand the basics of AI and is an opportunity to join the active and growing network of Women in AI. This recording is from the Session 4 of the AI Crash Course 2021 Spring Edition about Machine Learning & Deep Learning with Sheetal Reddy Hosts: Raquel Sanchez and Peter Kurzwelly from AI Sweden (https://www.ai.se/en​) Sofie Nabseth and Jonna Hillblom from Women in AI Sweden (https://www.womeninai.co/​) Expert: Anna Hjalmarsson, Electrolux Read more about the AI Crash Course here: https://www.ai.se/en/events/ai-crash-…
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)
Where are the opportunities? What markets and segments are tech entrepreneurs going after right now and why? Are there unique challenges for startups in this space? Albert Wenger, Union Square Ventures (Keynote Speaker) Fiona Murray, MIT (Panel Moderator) Cynthia Breazeal, MIT Stephane Kasriel, Upwork Alex “Sandy” Pentland, MIT IDE Daniela Rus, MIT
Learn about FourthBrain’s live online Machine Learning Engineer Program, meet our students and your Lead Instructors.
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This fast-paced webcast will cover the core content required to pass the CISSP® exam. Eric Conrad, lead author of MGT414: SANS Training Program for CISSP® Certification, as well as the CISSP® Study Guide (Syngress), will discuss cornerstone concepts that are threaded throughout the exam, with an eye towards “the exam” way. Eric Conrad Eric Conrad is the lead course author of MGT414: SANS Training Program for CISSP® Certification, and co-author of both SEC511: Continuous Monitoring and Security Operations and SEC542: Web App Penetration Testing and Ethical Hacking. Eric is also the lead author of the books the CISSP Study Guide, and the Eleventh Hour CISSP: Study Guide. Eric also blogs about information security at http://www.ericconrad.com.
SASTRA Day 1, Session 03 ATAL AICTE FDP on AI,ML u0026DL 2020 09 14 at 01 18 GMT 7 Workshop topics – Introduction to Artificial Intelligence – Introduction to Python – Introduction to Internet of Things(IoT) – Problem Formulations & Representations – Uninformed and Informed Search Algorithms – Knowledge Representation and different types of Knowledge Representation – Ontology Engineering – Fuzzy and Temporal Logic Systems – Natural Language Processing – Machine Learning and Deep Learning – Reinforcement Learning – Application and current trends of AI – Sample Problems – Case Studies & hands-on Coding using Python for the above topics Full playlist: https://www.youtube.com/playlist?list=PL7Ld-_6sF_dqunfOyV4TuztyvbbhxZWJO
April 13-14, 2021 – The NHGRI Genomic Data Science Working Group hosted Machine Learning in Genomics: Tools, Resources, Clinical Applications and Ethics. This virtual workshop highlights the opportunities and obstacles that occur when applying machine learning methods to basic genome sciences and genomic medicine. Workshop Agenda: https://www.genome.gov/event-calendar/Machine-Learning-in-Genomics-Tools-Resources-Clinical-Applications-and-Ethics ————— Welcome ————— Co-chairs: Trey Ideker, Ph.D., University of California San Diego Mark Craven, Ph.D., University of Wisconsin Speaker: Eric Green, M.D., Ph.D., Director, National Human Genome Research Institute ————– Keynote: ————– Moderator: Shannon McWeeney, Ph.D., Oregon Health and Sciences University Presenters: Eric Topol, M.D., Scripps Research Brad Malin, Ph.D., Vanderbilt University Medical Center Chapters: 0:00 – Start 0:09 – Welcome (Mark Craven) 0:52 – Welcome (Trey Ideker) 1:28 – Opening Remarks (Eric Green) 9:41 – Keynote Presentation (Eric Topol) 34:54 – Keynote Presentation (Brad Malin) 59:00 – Q&A Session with Shannon McWeeney, Eric Topol and Brad Malin
SASTRA Day 3, Session 01 ATAL AICTE FDP on AI,ML u0026DL 2020 09 15 at 20 34 GMT 7 Workshop topics – Introduction to Artificial Intelligence – Introduction to Python – Introduction to Internet of Things(IoT) – Problem Formulations & Representations – Uninformed and Informed Search Algorithms – Knowledge Representation and different types of Knowledge Representation – Ontology Engineering – Fuzzy and Temporal Logic Systems – Natural Language Processing – Machine Learning and Deep Learning – Reinforcement Learning – Application and current trends of AI – Sample Problems – Case Studies & hands-on Coding using Python for the above topics Full playlist: https://www.youtube.com/playlist?list=PL7Ld-_6sF_dqunfOyV4TuztyvbbhxZWJO
SASTRA Day 5, Session 03 ATAL AICTE FDP on AI,ML u0026DL 2020 09 18 at 01 07 GMT 7 Workshop topics – Introduction to Artificial Intelligence – Introduction to Python – Introduction to Internet of Things(IoT) – Problem Formulations & Representations – Uninformed and Informed Search Algorithms – Knowledge Representation and different types of Knowledge Representation – Ontology Engineering – Fuzzy and Temporal Logic Systems – Natural Language Processing – Machine Learning and Deep Learning – Reinforcement Learning – Application and current trends of AI – Sample Problems – Case Studies & hands-on Coding using Python for the above topics Full playlist: https://www.youtube.com/playlist?list=PL7Ld-_6sF_dqunfOyV4TuztyvbbhxZWJO
Breakout Session – IV White Paper – Artificial Intelligence and its Contributions to Overcome COVID-19 Canada India Healthcare Summit 2021 (“CIHS 2021”), organized on May 20-21, 2021 by Canada India Foundation (CIF) in partnership with Toronto Rehab Institute – University Health Network (UHN), Federation of Indian Chambers of Commerce and Industries (FICCI) and the Consulate General of India, Toronto, is taking place on May 20-21, 2021. The year-long paralysis of people’s mobility, caused by #COVID-19, necessitated the Summit to morph into a fully virtual event. Speakers from Canada, India and USA will be coming together on a Zoom conferencing platform to address the themes of #Pandemic Response and Initiatives, #Biotechnology and #Artificial Intelligence and their contributions to overcome COVID-19. #artificialintelleignce #AI #pandemic #canadaindia #canada #india #covid-19 #democraciesworkingtogether #technology #research #medical #virus #medicalresearch #health #innovation #ideas #cihs2021 #canadaindiahealthsummit2021 #CIHS2021 #healthforum #cif #UHN #FICCI #indiaincanada #indiaintoronto #indiainvancouver #canadainindia #hciottawa #healthsector #healthcollaboration #medical #education #research #innovation #healtheducation #hospitals
Start your Artificial Intelligence and Machine Learning journey by joining “Deep Learning and its applications : Beginners to Advance” course. The program builds a solid foundation from basics to advance by covering the most popular and widely used deep learning technologies and its applications. Interactive learning: that’s what we do, and we’d like to share that with you. Come explore your learning journey with us! For any support ,Please write us @ support@infyni.com, we will revert back within 48 Hours
Hosted by the Mechanical Engineering Graduate Students Association, College of Engineering, University of Washington, Seattle. Speaker(s) : Sahil Kommalapati (UW MSME’21) Alrick Cyril Dsouza (UW MSME’21) Workshop series description: The four sessions will particularly focus on Artificial Neural Networks, Convolutional Neural Networks, Generative Adversarial Networks and Bayesian Optimization with Hyper-parameter tuning techniques respectively. The primary goal of these workshops would be to expose the applicability of Artificial Intelligence models to our mechanical engineering community and enable immediate integration of these models into current research. These sessions are designed to be collaborative and focus on exercises that are particularly of interest to the mechanical engineering community. Description for this session: In the first section on our series, we will introduce Artificial Neural Networks (ANNs). We will go over a brief history of origins, the structure of the network, activation functions, loss functions, mini-batches, and training using back-propagation algorithm. The differences between training, testing and validation datasets are explored. All the executions are done using the Keras Python package, which enables us to easily execute these techniques without writing code from scratch. Towards the end of the session, we present a brief historical review of how ANNs have helped the mechanical engineering community and conclude with an interactive programming session. Timestamps: 0:00 – Introduction / Overview 4:45 – Introduction to the session 10:55 – Universal Approximation theorem 13:55 – Training neural networks 27:30 – Backpropogation 44:50 – Optimizing Neural Networks 59:30 – ANNs for Mechanical Engineering. 1:10:00 – Tutorial
2021-04-17 The topics covered are Matplotlib, Neural networks, Deep learning.