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nibble.ai weekly - Issue #22: Insights from Transform 2019, New fast.ai course for NLP, and more...

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This week's top pick is Venture Beat's Why do 87% of data science projects never make it into product
 

nibble.ai dispatch

July 25 · Issue #22 · View online
Curated essays about the future of Data Science. Production Data Science and learning resources for continuous learning. Covers Data Science, Data Engineering, MLOps & DataOps. Curated by people at https://nibble.ai/

This week’s top pick is Venture Beat’s Why do 87% of data science projects never make it into production.
Some insights from the conference Transform 2019.
If your competitors are applying AI, and they’re finding insight that allow them to accelerate, they’re going to peel away really, really quickly. Deborah Leff, CTO for data science and AI at IBM

If AI is the new electricity, should you bet on it now? (read below)
If AI is the new electricity, should you bet on it now? (read below)
Don’t Bet on AI (yet)
Behind the (quite) provocative title, an interesting read that stems from an analysis of 7000 “AI Startups”.
AI is the new electricity. It will transform industries. But like electricity, it will take decades. Today is 1882 in the world of AI, not 1925.
7 Fundamental Steps to Complete a Data Project
Becoming data-powered is first and foremost about learning the basic steps and following them to go from raw data to building a machine learning model, and ultimately to operationalization.
Data Science at the New York Times
A summary (+ video and transcript) of a session held by Chris Wiggins, Chief Data Scientist at The New York Times, where he talked about the process they use
Even better if you are what Eric Colson would call a “full stack” data scientist and you ship to prod, which means you actually push code that results in a live API, a live GUI, something that somebody else can put to work, and that is how data scientists really can add value in my experience.
The Death of Big Data and the Emergence of the Multi-Cloud Era
The Era of Big Data is coming to an end as the focus shifts from how we collect data to processing that data in real-time.
Big Data is now a business asset supporting the next eras of multi-cloud support, machine learning, and real-time analytics.
News
Lyft released an open-source dataset for autonomous driving
This a large-scale dataset featuring the raw sensor camera and LiDAR inputs as perceived by a fleet of multiple, high-end, autonomous vehicles in a bounded geographic area. lyft.com
Facebook open-source DLRM, a deep learning recommendation model
DLRM combines principles from both collaborative filtering and predictive analytics-based approaches. facebook.com
Learning resources
New fast.ai course: A code-first introduction to NLP
fast.ai released a new course aimed at NLP. Here are the links to the course, the youtube playlist and the github repository. fast.ai
Machine Learning Summer School 2019 tutorials
Machine Learning Summer School 2019 tutorials are available for free on github. sites.google.com
Logistic Regression from Bayes Theorem
A helpful look at the relationship between Bayes’ Theroem and logistic regression.
Learning about the relationship about Bayes Theorem and Logistic Regression should provide you with some pretty powerful insights into the way logistic regression really works. Plus, you’ll get a glimpse at generalized linear models. countbayesie.com
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