We are a group of startup engineers, research scientists, computational linguists, mathematicians, philosophers, and others interested in understanding the meaning of text, reasoning, and human intent through technology. We want to apply our understanding to building new businesses and improving overall human experience in the modern connected world. The MIND Stack explained: mind.wtf.
This is a technical AI meetup: we build systems with Machine Learning on top of Data Pipelines, and concern ourselves with the stuff we can try in open source, learn, improve, and model human behavior in industry for practical results.
The advisory board for this meetup is Cicero Institute (Cicero.ai), and its conferences are AI.vision and self.driving.cars. We like specific technical problems (self-driving cars) and the way they inform better higher-level inference of the future of AI (AI.vision).
We’re kicking off the year at our new partner venue, Microsoft Reactor!
Apache Spark™ is the dominant processing framework for big data. Delta Lake adds reliability to Spark so your analytics and machine learning initiatives have ready access to quality, reliable data. This session covers the use of Delta Lake to enhance data reliability for Spark environments.
The role of Apache Spark in big data processing
Use of data lakes as an important part of the data architecture
Data lake reliability challenges
How Delta Lake helps provide reliable data for Spark processing
Specific improvements that Delta Lake adds
The ease of adopting Delta Lake for powering your data lake
Chris Hoshino-Fish is a Solutions Architect at Databricks. Chris is an active member of the Performance Subject Matter Expert group and a former Principal Consultant focused on Data Engineering, working with several Fortune 500 Databricks customers. Prior to Databricks, Chris worked for an adtech company as a data engineer managing pipelines using Apache Spark for 3.5 years. Chris has a B.A. in Computational Mathematics from the University of California, Santa Cruz.
-- we'll open the floor for the rest of the meetup to the lightning talks proposed in the comments!
Note: the limits of Deep Learning will be examined by the AI industry leaders at http://ai.vision conference, San Francisco, March 8. Early Bird ends 12/31.
This is a biweekly reading group for the book by Goodfellow, Bengio and Courville (https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618).
We'll meet in 2017 and go through it in sequence. We need a fixed venue to host us -- please email Alexy at [masked] if you want to be the home of the brave AI. We'll need reading group leaders for this to happen, please email Alexy if you want to lead certain chapters or the whole sequence.