Applied Machine Learning Days (AMLD) is one of the largest Machine Learning & AI events in Europe, and the largest & best-known in Switzerland, focused specifically on the applications of Machine Learning and Artificial Intelligence, making it particularly interesting to industry, academia and public goods organizations.
Some of the speakers:
Garry Kasparov (Chess Grandmaster)
Zeynep Tufekci (New York Times writer on AI topics and social impacts of technology, and Prof at Harvard)
Jeff Dean (Head of AI Google, the lead of Google AI, co-inventor of MapReduce, TensorFlow and word2vec)
Katja Hofmann (Microsoft Research, Project Malmo Research Lead)
Antoine Bordes (Director Facebook AI Research Paris)
Alex “Sandy” Pentland (Serial entrepreneur, Co-Founder of the MIT Media Lab and among most cited authors in computer science)
Yuan (Alan) Qi (Vice President & AI Chief Scientist, Ant Financial)
Yuanchun Shi (Professor, Tsinghua University)
Christopher Bishop (Laboratory Director, Microsoft Research Cambridge)
The event will take place from January 26th to 29th, 2019, at the Swiss Tech Convention Center on EPFL campus, Lausanne, Switzerland, and expecting to have around 2000 visitors.
26+27 January: Saturday and Sunday will be ‘hands-on’ with more than 25 workshops, tutorials, training, coding classes and hackathons.
28+29 January: The main conference will take place on Monday and Tuesday, with a program featuring more than 230 amazing speakers, 16 domain-specific tracks (parallel session), poster sessions, a job fair and a special night with Garry Kasparov, who is recognised by many as the greatest chess player of all time. His legendary matches against the supercomputer Deep Blue made him a central figure in artificial intelligence and the evolution of the human-machine relationship.
Event website: https://www.appliedmldays.org/
Registration is mandatory, and it includes breakfast, coffee breaks, lunch and refreshments
Early bird tickets are half-price tickets, sales ends on 9th December 2018
Organised by the Founders of AMLD / EPFL Professors: Marcel Salathé, Martin Jaggi and Bob West
President of EPFL: Martin Vetterli
Contact: info@appliedmldays.org
Videos of AMLD2018 talks are available on AMLD’s YouTube channel
Topic tracks:
AI & Cities
AI & Computer Systems
AI & Environment
AI & Finance
AI & Health
AI & Industry
AI & Intellectual Property
AI & Language
AI & Learning Analytics
AI & Media
AI & the Molecular World
AI & Networks
AI & Nutrition
AI & Society
AI & Transportation
AI & Trust
Workshops:
Hands-on deep learning with TensorFlow.js
Policy-Making and Data Economy at the city level: utopia or reality?
Applied Language Technologies
Engineering for good – detecting pneumonia in X-Ray images
Advances in ML: Theory meets practice
AI and Healthcare
Industrial open data
Building Private-by-Design Voice Assistants with Snips
Trust In AI – methods and use cases for debiasing and explaining of algorithms
Using PySpark and interactive Jupyter notebook on Amazon Clusters
Tutorial: Build your first predictive model to forecast and detect anomalies
ML in your organization: a practical toolbox to identify and seize highest value opportunities in Machine Learning
PySpark: Big Data Processing and Machine Learning with Python
Enabling Resilience with Remote Sensing
Artificial Curiosity: Intrinsic Motivation in Machines too!
Reaching into the Rabbit Hole: Should we replace teachers with AI?
Machine Learning for fake news detection: theory and practice
TensorFlow Basics
Learning and Processing over Networks
Crash course in R for machine learning
Machine Learning Competition: Tennis Prediction
Applied Machine Learning for Anomaly Detection on Equipment
Credit Suisse Document Digitization Hackathon
TDA crash course: theory and practice for ML applications
Data exploration and preparation for Machine Learning
Machine Learning in Finance
Blue Brain Nexus, a knowledge graph for data-driven projects
Copyrights: EPFL & AMLD
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Some of the speakers:
Garry Kasparov (Chess Grandmaster)
Zeynep Tufekci (New York Times writer on AI topics and social impacts of technology, and Prof at Harvard)
Jeff Dean (Head of AI Google, the lead of Google AI, co-inventor of MapReduce, TensorFlow and word2vec)
Katja Hofmann (Microsoft Research, Project Malmo Research Lead)
Antoine Bordes (Director Facebook AI Research Paris)
Alex “Sandy” Pentland (Serial entrepreneur, Co-Founder of the MIT Media Lab and among most cited authors in computer science)
Yuan (Alan) Qi (Vice President & AI Chief Scientist, Ant Financial)
Yuanchun Shi (Professor, Tsinghua University)
Christopher Bishop (Laboratory Director, Microsoft Research Cambridge)
The event will take place from January 26th to 29th, 2019, at the Swiss Tech Convention Center on EPFL campus, Lausanne, Switzerland, and expecting to have around 2000 visitors.
26+27 January: Saturday and Sunday will be ‘hands-on’ with more than 25 workshops, tutorials, training, coding classes and hackathons.
28+29 January: The main conference will take place on Monday and Tuesday, with a program featuring more than 230 amazing speakers, 16 domain-specific tracks (parallel session), poster sessions, a job fair and a special night with Garry Kasparov, who is recognised by many as the greatest chess player of all time. His legendary matches against the supercomputer Deep Blue made him a central figure in artificial intelligence and the evolution of the human-machine relationship.
Event website: https://www.appliedmldays.org/
Registration is mandatory, and it includes breakfast, coffee breaks, lunch and refreshments
Early bird tickets are half-price tickets, sales ends on 9th December 2018
Organised by the Founders of AMLD / EPFL Professors: Marcel Salathé, Martin Jaggi and Bob West
President of EPFL: Martin Vetterli
Contact: info@appliedmldays.org
Videos of AMLD2018 talks are available on AMLD’s YouTube channel
Topic tracks:
AI & Cities
AI & Computer Systems
AI & Environment
AI & Finance
AI & Health
AI & Industry
AI & Intellectual Property
AI & Language
AI & Learning Analytics
AI & Media
AI & the Molecular World
AI & Networks
AI & Nutrition
AI & Society
AI & Transportation
AI & Trust
Workshops:
Hands-on deep learning with TensorFlow.js
Policy-Making and Data Economy at the city level: utopia or reality?
Applied Language Technologies
Engineering for good – detecting pneumonia in X-Ray images
Advances in ML: Theory meets practice
AI and Healthcare
Industrial open data
Building Private-by-Design Voice Assistants with Snips
Trust In AI – methods and use cases for debiasing and explaining of algorithms
Using PySpark and interactive Jupyter notebook on Amazon Clusters
Tutorial: Build your first predictive model to forecast and detect anomalies
ML in your organization: a practical toolbox to identify and seize highest value opportunities in Machine Learning
PySpark: Big Data Processing and Machine Learning with Python
Enabling Resilience with Remote Sensing
Artificial Curiosity: Intrinsic Motivation in Machines too!
Reaching into the Rabbit Hole: Should we replace teachers with AI?
Machine Learning for fake news detection: theory and practice
TensorFlow Basics
Learning and Processing over Networks
Crash course in R for machine learning
Machine Learning Competition: Tennis Prediction
Applied Machine Learning for Anomaly Detection on Equipment
Credit Suisse Document Digitization Hackathon
TDA crash course: theory and practice for ML applications
Data exploration and preparation for Machine Learning
Machine Learning in Finance
Blue Brain Nexus, a knowledge graph for data-driven projects
Copyrights: EPFL & AMLD
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
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