SASTRA Day 4, Session 01 ATAL AICTE FDP on AI,ML u0026DL 2020 09 16 at 20 42 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 01 ATAL AICTE FDP on AI,ML u0026DL 2020 09 17 at 20 35 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 4, Session 04 ATAL AICTE FDP on AI,ML u0026DL 2020 09 17 at 02 45 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

We have completed this four weeks journey of building the foundations of Artificial Intelligence with passionate learners.

This journey is just a start of taking you further on deeper understanding of concepts, hands-on projects, and datasets.

A special closed session with Dr.Shahid will be conducted on 4th Oct, 2020 who has successfully completed the course and attempted quizzes of topics.

Do share your course feedback here:
https://forms.gle/2iQKoo8bASoNf2U46

We will love to bring more learning material.

Keep Learning
Stay tuned for upcoming phase “Models of Machine Learning” a hands on journey!

Session 3: Machine Learning and Artificial Intelligence Tools

Real World Deployment
– Suchi Saria, Johns Hopkins University

Whether it is Google’s DeepMind Health or IBM’s Watson System, Artificial Intelligence is revolutionizing the field of medicine. Our interactions with some form of Artificial Intelligence are inevitable in today’s world.
Artificial Intelligence is surely the future of efficient, accurate and hopefully more empathetic medicine- be it conventional or Ayurveda. Join me tomorrow for the 4th Session of Ayurveda Thinkathon with my guest Suchana Seth to understand more! #AIinayurveda #machinelearningandayurveda #ayurvedaresearch #AIethics #responsiblemachinelearning #ayurveda

AI Social, Ethical, Policy and Legal Considerations

SKCET – ATAL FDP on Artificial Intelligence, Machine Learning and Genomics – Session 10

[CHEY-CSIS Joint Conference] Geopolitical Risks and Scientific Innovation
Session 1: Artificial Intelligence and Machine Learning: Data-Driven Techniques and Software Intensive Technologies

사회자 Moderator
AHN Jung Ho (Professor, Seoul National University)

발표자 Speakers
Lindsey SHEPPARD (Fellow, CSIS)
Jason BROWN (Director of Chief of Staff, U.S. Air Force Strategic Studies Group)
KIM Yoon (Chief Technology Officer, SKT)
PARK Byung Jin (Vice President, Advanced Defense Technology Research Institute)

최종현학술원과 CSIS는 4차 산업혁명의 다양한 기술진보가 국제정치와 지정학 리스크에 미치는 영향을 조망하고자 최종현학술원-CSIS 컨퍼런스를 공동 주최했다. 이번 컨퍼런스는 과학혁신과 지정학 리스크에 대한 단편적인 분석을 뛰어넘어 인공지능, 머신러닝, 신소재, 무인체계, 사이버보안, 우주기술 분야에서의 혁신과 그것이 가져올 국제질서의 변화를 집중 분석했다.

On Jan. 30-31, 2020, the Chey Institute for Advanced Studies and CSIS co-hosted the conference titled “Geopolitical Risks and Scientific Innovation.” This conference invited renowned experts and scholars from Korea and the United States to discuss the impact of scientific innovation on geopolitical risks, especially in Northeast Asia. Issues included artificial intelligence and machine learning (AI/ML), advanced materials and their implications for supply chain, unmanned systems and robotics, cyber security and blockchain, and space technologies.

A common goal for the brightest minds from Stanford and beyond: putting humanity at the center of AI. Watch the Stanford HumanAI Symposium, featuring Bill Gates, Kate Crawford, Reid Hoffman, California Governor Gavin Newsom and many more gathered to discuss our shared dream of a better future.

❤ If you care about the future just as much as we do, like, subscribe and share our channel! ❤

—–

Talks @ Amsterdam AI #2, 27.09.2016

► Camiel Verschoor from Brids.AI talking – “Using AI to push agriculture forward”

► Rodger Buyvoets from Crobox

—–

Amsterdam AI is part of the global applied AI community City AI. We are a community of AI practitioners across 40+ cities that share their challenges and lessons learned in applied AI. For that purpose we organize quarterly get-togethers that help you connect to your local artificial intelligence community.

—–

✔ Join the community! https://city.ai/

✔ More local engagement! https://amsterdam.city.ai/

✔ Daily insights https://twitter.com/cityai

✔ In-depth articles about AI ecosystems around the world https://medium.com/cityai

✔ Get in touch with other AI enthusiasts https://www.facebook.com/cityai

14:00-14:20 Jes Frellsen, University of Cambridge Bayesian generalised ensemble Markov chain Monte Carlo
14:20-14:40 Adam Scibior, University of Cambridge Probabilistic programming with effect systems
14:40-15:00 Andy Gordon, Microsoft Research Fabular: Regression Formulas as Probabilistic Programming
15:00-15:20 John Hong, University of Cambridge Comparing Matrix Factorization algorithms on a level playing field

16:00-16:20 Alex Matthews, University of Cambridge A variational framework for approximate Gaussian process inference
16:20-16:40 Ferenc Huszár, Magic Pony Technology, Cambridge Generative Models for Image Processing
16:40-17:00 Sacha Krstulovic, Audio Analytic Ltd., Cambridge Automatic Environmental Sound Recognition: Performance versus Computational Cost

11:30-11:50 Antonio Criminisi, Microsoft Research Efficient machine learning for the quantitative analysis of medical images
11:50-12:10 Sebastian Nowozin, Microsoft Research Bayesian Time-of-Flight for Realtime Scene Decomposition into Geometry, Reflectance, and Light
12:10-12:30 Ryota Tomioka, Microsoft Research Understanding the role of invariances in training neural networks
12:30-12:50 Yoram Bachrach, Microsoft Research Analyzing factors behind hiring decisions based on online social network profiles

09:30-09:50 Carl Rasmussen, University of Cambridge Variational Inference in Gaussian Processes for non-linear time series
09:50-10:10 Yingzhen Li, University of Cambridge Variational inference with Rényi divergencee
10:10-10:30 Thang Bui, University of Cambridge Deep Gaussian Processes for Regression using Approximate Expectation Propagation
10:30-10:50 Adrian Weller, University of Cambridge Clamping variables and approximate inference

DARPA SUPERHIT 2021 Play Now!Close

DARPA SUPERHIT 2021

(StoneBridge Mix)

Play Now!

×