A while ago, I wrote a review of The Data Incubator based on my experience in the program. Since then, it’s been the most common reason people reach out to me. I’ve had people reach out to tell me how the program went for them, to ask me questions about the program, or to ask advice. Since this happens so frequently, and my review is a bit out of date now, I figured I would write an updated version, taking into account what has changed (and what hasn’t) according to those who have been through the program after me. I’ve also written a collection of the most common questions I get asked about the program, with my answers.
How to Use FPGAs for Deep Learning Inference to Perform Land Cover Mapping on Terabytes of Aerial Images
This post is authored by Mary Wahl, Data Scientist; Daniel Hartl and Wilson Lee, Senior Software Engineers; Xiaoyong Zhu, Program Manager; Erika Menezes, Software Engineer; and Wee Hyong Tok, Principal Data Scientist Manager, at Microsoft.
Summer of Data Science 2018
Memorial Day is the unofficial start of summer in the U.S., so in the past, we’ve also used it as the start date for the Summer of Data Science! The main goal of the Summer of Data Science is to learn something new during a fixed period of time, and share your progress and references to help and inspire others (and to get help from and get inspired by others, too!). If you want to learn more about the origin and history of the hashtag, I gave more background in last year’s post.
Image Compression using K-means Clustering.
This article illustrates one of the practical applications of K-means clustering algorithms. Using the K-means technique, we can compress the colored image using its pixel values.
“Creating correct and capable classifiers” at PyDataAmsterdam 2018
This weekend I got to attend PyDataAmsterdam 2018 – this is my first trip to the Netherlands (Yay! It is lovely here). The conference grew on last year to 345 attendees with over 20% female speakers.
What's New in Dataquest v1.85： Takeaways, Intermediate R, and More
How digital cameras work
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Context Compatibility in Data Analysis
Roger Peng ** 2018/05/24
Why Lies Spread Faster than the Truth
Light FM Recommendation System Explained
In my last article, I presented a brief overview of the three major kinds of recommendation systems: content-based methods, collaborative filtering, and hybrid models. I also introduced a recent model by the fashion company Lyst called Light FM, which combines product metadata, customer information, and transaction history through a latent space to come up with recommendations for customers.