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Applied Machine Learning Days 2019


Event details

Date and time 26.01.2019 29.01.2019  
Place and room
Speaker See our workshop sessions, the 16 featured tracks and the list of speakers.
Category Conferences - Seminars

The Applied Machine Learning Days will take place from January 26th to 29th, 2019, at the Swiss Tech Convention Center on EPFL campus. It is now the largest and best-known Machine Learning event in Switzerland, and increasingly recognized as a major event in Europe. The event has a focus specifically on the applications of machine learning and AI, making it particularly interesting to industry and academia.

Saturday & Sunday will be ‘hands-on’ with more than 25 workshops, tutorials, trainings, coding classes and hackathons. The main conference will take place on Monday and Tuesday, with a program featuring amazing speakers, 16 domain-specific tracks (parallel session), poster sessions, a job fair and a special night with Garry Kasparov.

- Garry Kasparov (Chess Grandmaster) 
- Zeynep Tufekci (The New York Times) 
- Jeff Dean (Google) 
- Katja Hofmann (Microsoft Research) 
- Antoine Bordes (Facebook AI Research) 
- Alex "Sandy" Pentland (MIT Media Lab) 
- Yuan (Alan) Qi (Ant Financial) 
- Yuanchun Shi (Tsinghua University) 
- Li Pu (Segway Robotics) 
- Christopher Bishop (Microsoft Research) 
- Evgeniy Gabrilovich (Google) 
- crowdAI winners

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! / Reatching into the Rabbit Hole: Should we replace teachers with AI? / Machine Learning for fake news detection: theory and practice / TensorFlow Basics - Saturday / TensorFlow Basics - Sunday / Learning and Processing over Networks / Crashcourse 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

• 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

Registration is mandatory and includes breakfast, coffee breaks, lunch and refreshments.

Practical information

  • Informed public
  • Registration required