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The Practical Quant's Blog

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Labeling, transforming, and structuring training data sets for machine learning

August 15, 2019 Comments (0)

The O'Reilly Data Show Podcast: Alex Ratner on how to build and manage training data with Snorkel.In this episode of the Data Show, I speak with Alex Ratner, project lead for Stanford’s Snorkel open source project; Ratner also recently garnered a faculty position at the University of Washington and is currently working on a company supporting and extending the Snorkel project. Snorkel is a framework for building and managing training data. Based on our survey from earlier this year, labeled...

Got speech? These guidelines will help you get started building voice applications

August 8, 2019 Comments (0)

Speech adds another level of complexity to AI applications - today’s voice applications provide a very early glimpse of what is to come.By Ben Lorica and Yishay Carmiel.As companies begin to explore AI technologies, three areas in particular are garnering a lot of attention: computer vision, natural language applications, and speech technologies. A recent report from the World Intellectual Patent Office (WIPO) found that together these three areas accounted for a majority of patents...

Make data science more useful

August 1, 2019 Comments (0)

The O'Reilly Data Show Podcast: Cassie Kozyrkov on connecting data and AI to business.In this episode of the Data Show, I speak with Cassie Kozyrkov, technical director and chief decision scientist at Google Cloud. She describes "decision intelligence" as an interdisciplinary field concerned with all aspects of decision-making, and which combines data science with the behavioral sciences. Most recently she has been focused on developing best practices that can help practitioners make safe,...

One simple graphic: Researchers love PyTorch and TensorFlow

July 25, 2019 Comments (0)

Interest in PyTorch among researchers is growing rapidly.In a recent survey—AI Adoption in the Enterprise, which drew more than 1,300 respondents—we found significant usage of several machine learning (ML) libraries and frameworks. About half indicated they used TensorFlow or scikit-learn, and a third reported they were using PyTorch or Keras.I recently attended an interesting RISELab presentation delivered by Caroline Lemieux describing recent work on AutoPandas and automation tools that rely...

Acquiring and sharing high-quality data

July 18, 2019 Comments (0)

The O'Reilly Data Show Podcast: Roger Chen on the fair value and decentralized governance of data.In this episode of the Data Show, I spoke with Roger Chen, co-founder and CEO of Computable Labs, a startup focused on building tools for the creation of data networks and data exchanges. Chen has also served as co-chair of O'Reilly's Artificial Intelligence Conference since its inception in 2016. This conversation took place the day after Chen and his collaborators released an...

You'll want Nexar's newly released Live Map for your city

July 17, 2019 Comments (0)

Extracting and exposing valuable insights to enable smart cities and many other applications.I recently had the privilege of getting a preview of Nexar's Live Map, from my friend, Nexar's CTO and co-founder Bruno Fernandez-Ruiz. Nexar uses off-the-shelf smartphones and dash-cams, sophisticated data ingestion, data processing, sensor fusion, and machine learning software to realize their vision of creating the largest safe driving network. To date the company has recorded many miles of driving...

Managing machine learning in the enterprise: Lessons from banking and health care

July 15, 2019 Comments (0)

A look at how guidelines from regulated industries can help shape your ML strategy.By Ben Lorica, Harish Doddi, David Talby.As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model...

Tools for machine learning development

July 3, 2019 Comments (0)

The O'Reilly Data Show: Ben Lorica chats with Jeff Meyerson of Software Engineering Daily about data engineering, data architecture and infrastructure, and machine learning.By Jenn Webb.In this week's episode of the Data Show, we're featuring an interview Data Show host Ben Lorica participated in for the Software Engineering Daily Podcast, where he was interviewed by Jeff Meyerson. Their conversation mainly centered around data engineering, data architecture and infrastructure, and machine...

RISELab’s AutoPandas hints at automation tech that will change the nature of software development

July 1, 2019 Comments (0)

Neural-backed generators are a promising step toward practical program synthesis.There's a lot of hype surrounding AI, but are companies actually beginning to use AI technologies? In a survey we released earlier this year, we found that more than 60% of respondents worked in organizations that planned to invest some of their IT budgets into AI. We also found that the level of investment depended on how much experience a company already had with AI technologies, with companies further along the...

One simple chart: Who is interested in Spark NLP?

June 27, 2019 Comments (0)

As we close in on its two-year anniversary, Spark NLP is proving itself a viable option for enterprise use.In July 2016, I broached the idea for an NLP library aimed at Apache Spark users to my friend David Talby. A little over a year later, Talby and his collaborators announced the release of Spark NLP. They described the motivation behind the project in their announcement post and in this accompanying podcast that Talby and I wrote, as well as in this recent post comparing popular open source...