Mar 15–18, 2020

Schedule: Data Science and Machine Learning sessions

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9:00am12:30pm Monday, March 16, 2020
Location: LL21A
Alice Zhao (Metis)
Data scientists are known to crunch numbers, but you may also run into text data. Alice Zhao teaches you to turn text data into a format that a machine can understand, identifies some of the most popular text analytics techniques, and showcases several natural language processing (NLP) libraries in Python including the natural language toolkit (NLTK), TextBlob, spaCy, and gensim. Read more.
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9:00am12:30pm Monday, March 16, 2020
Location: LL21 C
Sourav Dey (Manifold), Alex Ng (Manifold)
ML engineers work at the intersection of data science and software engineering—that is, MLOps. Sourav Dey and Alex Ng highlight the six steps of the Lean AI process and explain how it helps ML engineers work as an integrated part of development and production teams. You'll go hands-on with real-world data so you can get up and running seamlessly. Read more.
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9:00am5:00pm Monday, March 16, 2020
Location: LL20A
Jeffrey Vah (Dell Technologies), Gayathri Rau (Dell Technologies), Shuo Xiang (Robinhood), Maureen Teyssier (Reonomy), Aaron Williams (OmniSci), Sriram Ravindran (Adobe Inc), Deepak Pai (Adobe), Shubranshu Shekhar (Carnegie Mellon University), Sherin Thomas (Lyft), Dan Gifford (Getty Images), Shondria Lopez-Merlos (Florida Conference of The United Methodist Church), Sandhya Raghavan (Virgin Hyperloop One), Patryk Oleniuk (Virgin Hyperloop One), Ian Beaver (Verint - Next IT), Aryn Sargent (Verint)
From banking to biotech, retail to government, every business sector is changing in the face of abundant data. Get better at defining business problems and applying data solutions at Strata Data & AI. Read more.
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1:30pm5:00pm Monday, March 16, 2020
Location: LL20D
Robert Nishihara (University of California, Berkeley), Ion Stoica (University of California, Berkeley), Philipp Moritz (University of California, Berkeley)
There's no easy way to scale up Python applications to the cloud. Ray is an open source framework for parallel and distributed computing, making it easy to program and analyze data at any scale by providing general-purpose high-performance primitives. Robert Nishihara, Ion Stoica, and Philipp Moritz demonstrate how to use Ray to scale up Python applications, data processing, and machine learning. Read more.
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1:30pm5:00pm Monday, March 16, 2020
Location: LL21A
David Talby (Pacific AI), Alex Thomas (John Snow Labs), Claudiu Branzan (Accenture), Veysel Kocaman (John Snow Labs)
David Talby, Alex Thomas, and Claudiu Branzan detail the application of the latest advances in deep learning for common natural language processing (NLP) tasks such as named entity recognition, document classification, sentiment analysis, spell checking, and OCR. You'll learn to build complete text analysis pipelines using the highly performant, scalable, open source Spark NLP library in Python. Read more.

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