The annual AI NEXTCon is coming up on Feb. 12~16, 2020 in Seattle. Continue reading “AI NEXTCon Developers Conference 2020 Seattle”
A quick introduction into Dimension Reduction, including a few widely used techniques, linear discriminant analysis, principal component analysis, kernel principal component analysis, and more. Continue reading “What Is Dimension Reduction in Machine Learning”
The annual AI NEXTCon is coming up on January 23rd-26th, 2019 in Seattle. Continue reading “AI NEXTCon Conference Seattle 2019”
A laundry list of personal reminders on software development process, API design, and developers career. by Francois Chollet. 5mins read. Continue reading “Speaker Post: Notes to myself on software engineering”
I’m going to show you what I thought were the 10 coolest papers at CVPR 2018. We’ll see new applications that have only recently been made possible by using deep networks, and others that offer a new twist on how to use them. 10mins read.
Continue reading “The Top 10 papers from CVPR 2018”
Any solution to the shortage of machine learning expertise requires answering this question: whether it’s so we know what skills to teach, what tools to build, or what processes to automate. 10mins read.
Continue reading “What machine learning engineers really do?”
I show how with a few clicks I was able to visually drill down into the transactions, where I find all the million dollar transactions that involve the top 100 popular bitcoin addresses. by Vedar Shanker. 10mins read.
Continue reading “Speaker post: Bitcoin Transactions: From BigQuery to MapD”
steps by steps on how to prepare data science interview with practical advices. by Brandon Rohrer, data scientist at Facebook. 15mins read Continue reading “Speaker Post: How to survive your data science interview”
full of specific actions to take, not just abstract ideals on how we analyze large and complex data sets in Google. by Partick Riley. 10mins read.
Continue reading “Google Data Analysis: practical advice for analysis of large, complex data sets”
This document is intended to help those with a basic knowledge of machine learning get the benefit of Google’s best practices in machine learning. phase 3: Grow, optimization, complex models. 8 mins read.