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The Practical Quant's Blog

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Simplifying machine learning lifecycle management

August 16, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Harish Doddi on accelerating the path from prototype to production.In this episode of the Data Show, I spoke with Harish Doddi, co-founder and CEO of Datatron, a startup focused on helping companies deploy and manage machine learning models. As companies move from machine learning prototypes to products and services, tools and best practices for productionizing and managing models are just starting to emerge....

Notes from the first Ray meetup

August 15, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]Ray is beginning to be used to power large-scale, real-time AI applications.Machine learning adoption is accelerating due to the growing number of large labeled data sets, languages aimed at data scientists (R, Julia, Python), frameworks (scikit-learn, PyTorch, TensorFlow, etc.), and tools for building infrastructure to support end-to-end applications. While some interesting applications of unsupervised learning are beginning to emerge,...

How privacy-preserving techniques can lead to more robust machine learning models

August 2, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Chang Liu on operations research, and the interplay between differential privacy and machine learning.In this episode of the Data Show, I spoke with Chang Liu, applied research scientist at Georgian Partners. In a previous post, I highlighted early tools for privacy-preserving analytics, both for improving decision-making (business intelligence and analytics) and for enabling automation (machine learning)....

Specialized hardware for deep learning will unleash innovation

July 19, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Andrew Feldman on why deep learning is ushering a golden age for compute architecture.In this episode of the Data Show, I spoke with Andrew Feldman, founder and CEO of Cerebras Systems, a startup in the blossoming area of specialized hardware for machine learning. Since the release of AlexNet in 2012, we have seen an explosion in activity in machine learning, particularly in deep learning. A lot of the work...

Data collection and data markets in the age of privacy and machine learning

July 18, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]While models and algorithms garner most of the media coverage, this is a great time to be thinking about building tools in data.In this post I share slides and notes from a keynote I gave at the Strata Data Conference in London at the end of May. My goal was to remind the data community about the many interesting opportunities and challenges in data itself. Much of the focus of recent press coverage has been on algorithms and models,...

What machine learning means for software development

July 11, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]"Human in the loop" software development will be a big part of the future.Machine learning is poised to change the nature of software development in fundamental ways, perhaps for the first time since the invention of FORTRAN and LISP. It presents the first real challenge to our decades-old paradigms for programming. What will these changes mean for the millions of people who are now practicing software development? Will we see job losses...

Data regulations and privacy discussions are still in the early stages

July 5, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Aurélie Pols on GDPR, ethics, and ePrivacy.In this episode of the Data Show, I spoke with Aurélie Pols of Mind Your Privacy, one of my go-to resources when it comes to data privacy and data ethics. This interview took place at Strata Data London, a couple of days before the EU General Data Protection Regulation (GDPR) took effect. I wanted her perspective on this landmark regulation, as well as her take on...

Managing risk in machine learning models

July 5, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Andrew Burt and Steven Touw on how companies can manage models they cannot fully explain.In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer at Immuta, and Steven Touw, co-founder and CTO of Immuta. Burt recently co-authored a white paper on managing risk in machine learning models, and I wanted to sit down with them to discuss some of the proposals they put forward to...

Understanding automation

July 5, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]An overview and framework, including tools that can be used to enable automation.In this post, I share slides and notes from a talk Roger Chen and I gavein May 2018 at the Artificial Intelligence Conference in New York. Most companies are beginning to explore how to use machine learning and AI, and we wanted to give an overview and framework for how to think about these technologies and their roles in automation. Along the way, we describe...

The real value of data requires a holistic view of the end-to-end data pipeline

July 5, 2018 Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Ashok Srivastava on the emergence of machine learning and AI for enterprise applications.In this episode of the Data Show, I spoke with Ashok Srivastava, senior vice president and chief data officer at Intuit. He has a strong science and engineering background, combined with years of applying machine learning and data science in industry. Prior to joining Intuit, he led the teams responsible for data and...