To become a “machine learning company,” you need tools and processes to overcome challenges in data, engineering, and models. Over the last few years, the data community has focused on gathering and collecting data, building infrastructure for that purpose, and using data to improve decision-making. We are now seeing a surge in interest in advancedContinue reading “How companies can navigate the age of machine learning”
Category Archives: Data Science
Transforming organizations through analytics centers of excellence
[A version of this post appears on the O’Reilly Radar blog.] The O’Reilly Data Show Podcast: Carme Artigas on helping enterprises transform themselves with big data tools and technologies. In this episode of the Data Show, I spoke with Carme Artigas, co-founder and CEO of Synergic Partners (a Telefonica company). As more companies adopt bigContinue reading “Transforming organizations through analytics centers of excellence”
The state of machine learning in Apache Spark
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Ion Stoica and Matei Zaharia explore the rich ecosystem of analytic tools around Apache Spark. In this episode of the Data Show, we look back to a recent conversation I had at the Spark Summit in San Francisco with IonContinue reading “The state of machine learning in Apache Spark”
The current state of applied data science
[A version of this post appears on the O’Reilly Radar.] Recent trends in practical use and a discussion of key bottlenecks in supervised machine learning. As we enter the latter part of 2017, it’s time to take a look at the common challenges faced by companies interested in using data science and machine learning (ML).Continue reading “The current state of applied data science”
A framework for building and evaluating data products
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Pinterest data scientist Grace Huang on lessons learned in the course of machine learning product launches. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher,Continue reading “A framework for building and evaluating data products”
Programming collective intelligence for financial trading
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Geoffrey Bradway on building a trading system that synthesizes many different models. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS.Continue reading “Programming collective intelligence for financial trading”
Creating large training data sets quickly
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Alex Ratner on why weak supervision is the key to unlocking dark data. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud,Continue reading “Creating large training data sets quickly”
What are machine learning engineers?
[A version of this appears on the O’Reilly Radar.] A new role focused on creating data products and making data science work in production. by Ben Lorica and Mike Loukides We’ve been talking about data science and data scientists for a decade now. While there’s always been some debate over what “data scientist” means, we’veContinue reading “What are machine learning engineers?”
Data science and deep learning in retail
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Jeremy Stanley on hiring and leading machine learning engineers to build world-class data products. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes,Continue reading “Data science and deep learning in retail”
Data preparation in the age of deep learning
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Lukas Biewald on why companies are spending millions of dollars on labeled data sets. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes,Continue reading “Data preparation in the age of deep learning”