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The Practical Quant's Blog

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The current state of Apache Kafka

November 22, 2017 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Neha Narkhede on data integration, microservices, and Kafka’s roadmap.In this episode of the Data Show, I spoke with Neha Narkhede, co-founder and CTO of Confluent. As I noted in a recent post on “The Age of Machine Learning,” data integration and data enrichment are non-trivial and ongoing challenges for most companies. Getting data ready for analytics—including machine learning—remains an area of focus for...

Building a natural language processing library for Apache Spark

November 9, 2017 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: David Talby on a new NLP library for Spark, and why model development starts after a model gets deployed to production.When I first discovered and started using Apache Spark, a majority of the use cases I used it for involved unstructured text. The absence of libraries meant rolling my own NLP utilities, and, in many cases, implementing a machine learning library (this was pre deep learning, and MLlib was...

Machine intelligence for content distribution, logistics, smarter cities, and more

October 26, 2017 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Rhea Liu on technology trends in China.In this episode of the Data Show, I spoke with Rhea Liu, analyst at China Tech Insights, a new research firm that is part of Tencent’s Online Media Group. If there’s one place where AI and machine learning are discussed even more than the San Francisco Bay Area, that would be China. Each time I go to China, there are new applications that weren’t widely available just...

How companies can navigate the age of machine learning

October 24, 2017 Comments (0)

[A version of this post appears on the O'Reilly Radar.]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 advanced analytics and machine learning across many industry verticals.In this post, I share slides and...

Vehicle-to-vehicle communication networks can help fuel smart cities

October 12, 2017 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Bruno Fernandez-Ruiz on the importance of building the ground control center of the future.In this episode of the Data Show, I spoke with Bruno Fernandez-Ruiz, co-founder and CTO of Nexar. We first met when he was leading Yahoo! technical teams charged with delivering a variety of large-scale, real-time data products. His new company is helping build out critical infrastructure for the emerging transportation...

Transforming organizations through analytics centers of excellence

September 28, 2017 Comments (0)

[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 big data technologies and techniques, it’s useful to remember that the end goal is to extract information and insight. In fact, as with any collection of tools...

The state of machine learning in Apache Spark

September 14, 2017 Comments (0)

[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 Ion Stoica (UC Berkeley professor and executive chairman of Databricks) and Matei Zaharia (assistant professor at Stanford and chief technologist of Databricks). Stoica and Zaharia were core members...

Effective mechanisms for searching the space of machine learning algorithms

August 31, 2017 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Kenneth Stanley on neuroevolution and other principled ways of exploring the world without an objective.In this episode of the Data Show, I spoke with Ken Stanley, founding member of Uber AI Labs and associate professor at the University of Central Florida. Stanley is an AI researcher and a leading pioneer in the field of neuroevolution—a method for evolving and learning neural networks through evolutionary...

The current state of applied data science

August 24, 2017 Comments (0)

[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). Let’s assume your organization is already collecting data at a scale that justifies the use of analytic tools, and that you’ve managed to identify and prioritize use cases where...

The current state of applied data science

August 24, 2017 Comments (0)

[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). Let’s assume your organization is already collecting data at a scale that justifies the use of analytic tools, and that you’ve managed to identify and prioritize use cases where...