ML Kitchen #2:


Details
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Whether you're working on machine learning during the day or in your free time, take this opportunity to meet other researchers and engineers. Good chance to converge, add some noise to your neurons, network with your peers, get some knowledge transfer and go deeper into machine learning topics with interesting talks.
Also, since this is Cookpad, there will be awesome food and drinks!
Schedule:
19:15 - Doors Open, networking
19:30 - Drinks, food
20:00 - "Current methods and models for visual prediction." by Evan C.
20:30 - Break
21:00 - "Real time data pipeline for anomaly detection" (https://www.slideshare.net/mathieudumoulin2/predictive-analytics-with-streaming-sensor-data) by Mathieu Dumoulin
21:30 - "Why and how does deep learning work well? From some theoretical point of view." by Yohei Kikuta (https://www.linkedin.com/in/yohei-kikuta-983b29117)
22:00 - Close

ML Kitchen #2: