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Data Science Weekly Newsletter
February 28, 2019
Ever wondered whether it's possible to measure the similarity between sets of ingredients in cocktails so you can conceptualize drinks in a connected graph, in which edges represent substitutions? No? well,...
Humanity + AI: Better Together
So the counter-narrative I want to offer to the mainstream, front page accounts is that with careful, thoughtful, empathic design, we can enable ourselves to live longer, safer lives. We can create jobs where we are doing more creative work. We can understand each other better. But before I get to the many, many examples of where this is already happening today, let me share what’s happening in the AI ecosystem more broadly...
After helping hundred of readers like you get Data Science jobs, we've distilled all the real-world-tested advice into a self-directed course.
The course is broken down into three guides:
Data Science Getting Started Guide. This guide shows you how to figure out the knowledge gaps that MUST be closed in order for you to become a data scientist quickly and effectively (as well as the ones you can ignore)
Data Science Project Portfolio Guide. This guide teaches you how to start, structure, and develop your data science portfolio with the right goals and direction so that you are a hiring manager's dream candidate
Data Science Resume Guide. This guide shows how to make your resume promote your best parts, what to leave out, how to tailor it to each job you want, as well as how to make your cover letter so good it can't be ignored!
Fixup Initialization: Residual Learning Without Normalization
Normalization layers are a staple in state-of-the-art deep neural network architectures. They are widely believed to stabilize training, enable higher learning rate, accelerate convergence and improve generalization, though the reason for their effectiveness is still an active research topic. In this work, we challenge the commonly-held beliefs by showing that none of the perceived benefits is unique to normalization. Specifically, we propose fixed-update initialization (Fixup), an initialization motivated by solving the exploding and vanishing gradient problem at the beginning of training via properly rescaling a standard initialization...
Paper: Parsing Gigabytes of JSON per Second
Daniel Lemire and I have spent some time this year working on a fast JSON parser. In this blog post, I’ll provide an informal summary of the paper and some background as to the thinking behind the system...
The MIT Robo-AI Exchange (March 9, 2019) will bring together business leaders from across a number of industries to share strategies and outcomes related to the adoption of Robotics and AI. The event attracts business executives, corporate strategists, product and project managers, university students, entrepreneurs, technologists and academics to learn from world-class keynote speakers and panelists as well as one another.
Use promo code BNT982 at https://robo-ai.org for 20% off professional tickets.
Want to post an event here? Email us for details >> firstname.lastname@example.org
The Data Scientist is a critical position within DSS and in the Data organization who specializes in applying machine learning methods to meet optimization, personalization, recommendations and efficiency related challenges, in close collaboration with engineering and business partners. In this role, you will build and apply machine learning techniques and modern statistics to data both augment decision-making but to also significantly improve operational process problems through automation. You will collaborate across teams to define problems and develop automated solutions with the Data, Product and Engineering teams to be built into our products...
Want to post a job here? Email us for details >> email@example.com
Training & Resources
Print TensorFlow Version
Learn how to find out which version of TensorFlow is installed in your system by printing the TensorFlow version, via a screencast video and full tutorial transcript...
The Book of R: A First Course in Programming and Statistics
"The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis"...
For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page .