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The Practical Quant wrote a new blog post titled Responsible deployment of machine learning
[A version of this post appears on the O'Reilly Radar.]We need to build machine learning tools to augment our machine learning engineers.In this post, I share slides and notes from a talk I gave in December 2017 at the Strata Data Conference in Singapore offering suggestions to companies that are actively deploying products infused with machine learning capabilities. Over the past few years, the data community has focused on infrastructure and platforms for data collection, including robust pipelines and highly scalable storage systems for analytics. According to a recent LinkedIn report, the...
6 days ago
The Practical Quant wrote a new blog post titled What lies ahead for data in 2018
[A version of this post appears on the O'Reilly Radar.]How new developments in algorithms, machine learning, analytics, infrastructure, data ethics, and culture will shape data in 2018.1. New tools will make graphs and time series easier, leading to new use casesGraphs and time series have been a crucial part of the explosion in big data. 2018 will see the emergence of a new generation of tools for storing and analyzing graphs and time series at large scale. These new analytic and visualization tools will help product groups devise new offerings, especially for use cases in security and fraud...
8 days ago
The Practical Quant wrote a new blog post titled 5 AI trends to watch in 2018
[A version of this post appears on the O'Reilly Radar.]Expect substantial progress in machine learning methods, understanding, and pedagogyAs in recent years, new deep learning architectures and (distributed) training algorithms will lead to impressive results and applications in a range of domains, including computer vision, speech, and text. Expect to see companies make progress on efficient algorithms for training, inference, and data processing on edge devices. At the same time, collaboration between machine learning experts will produce interesting breakthroughs—examples include work...
8 days ago
The Practical Quant wrote a new blog post titled 8 fintech trends for 2018
[A version of this post appears on the O'Reilly Radar.]AI, blockchain, payment regionalization, and other fintech trends to watch.2017 saw big changes, a lot of investment, and some regulatory challenges in fintech. What will 2018 bring? Here’s what we’ll be watching in the coming year.1. AI will be implemented across the stackAI is sweeping across all industry sectors, including financial services. AI touches customer interactions (voice services like Siri and dialog systems), fraud detection, trading, and risk management (machine learning), and is being used to automate many back-office...
9 days ago
The Practical Quant wrote a new blog post titled Bringing AI into the enterprise
[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Kris Hammond on business applications of AI technologies and educating future AI specialists.In this episode of the Data Show, I spoke with Kristian Hammond, chief scientist of Narrative Science and professor of EECS at Northwestern University. He has been at the forefront of helping companies understand the power, limitations, and disruptive potential of AI technologies and tools. In a previous post on machine learning, I listed types of uses cases (a taxonomy) for machine learning that could just as well...
13 days ago
The Practical Quant wrote a new blog post titled How machine learning will accelerate data management systems
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Tim Kraska on why ML will change how we build core algorithms and data structures.In this episode of the Data Show, I spoke with Tim Kraska, associate professor of computer science at MIT. To take advantage of big data, we need scalable, fast, and efficient data management systems. Database administrators and users often find themselves tasked with building index structures (“indexes” in database parlance), which are needed to speed up data access.Some common examples include:B-Trees—used for range requests...
27 days ago
The Practical Quant wrote a new blog post titled The state of AI adoption
[A version of this post appears on the O'Reilly Radar.]An overview of adoption, and suggestions to companies interested in AI technologies.Artificial intelligence (AI) has attracted a lot of media coverage recently, and companies are rushing to figure out how AI technologies will impact them. Much of the coverage is devoted to research breakthroughs or new product offerings. But how are companies integrating AI into their underlying businesses? In this post, we share slides and notes from a talk we gave this past September at the AI Conference in San Francisco, offering an overview of the...
30 days ago
The Practical Quant wrote a new blog post titled Practical applications of reinforcement learning in industry
[A version of this post appears on the O'Reilly Radar.]An overview of commercial and industrial applications of reinforcement learning.The flurry of headlines surrounding AlphaGo Zero (the most recent version of DeepMind’s AI system for playing Go) means interest in reinforcement learning (RL) is bound to increase. Next to deep learning, RL is among the most followed topics in AI. For most companies, RL is something to investigate and evaluate but few organizations have identified use cases where RL may play a role. As we enter 2018, I want to briefly describe areas where RL has been...
34 days ago
The Practical Quant wrote a new blog post titled Machine learning at Spotify: You are what you stream
[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Christine Hung on using data to drive digital transformation and recommenders that increase user engagement.In this episode of the Data Show, I spoke with Christine Hung, head of data solutions at Spotify. Prior to joining Spotify, she led data teams at the NY Times and at Apple (iTunes). Having led teams at three different companies, I wanted to hear her thoughts on digital transformation, and I wanted to know how she approaches the challenge of building, managing, and nurturing data teams.I also wanted to...
41 days ago
The Practical Quant wrote a new blog post titled The current state of Apache Kafka
[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 most companies. It turns out, “data lakes” have become staging grounds for data; more refinement...
56 days ago
The Practical Quant wrote a new blog post titled Building a natural language processing library for Apache Spark
[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 much smaller). I’d always wondered why no one bothered to create an NLP library for Spark when many...
69 days ago
The Practical Quant wrote a new blog post titled Machine intelligence for content distribution, logistics, smarter cities, and more
[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 the year before. This year, it was impossible to miss bike sharing, mobile payments seemed to be...
83 days ago
The Practical Quant wrote a new blog post titled How companies can navigate the age of machine learning
[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 notes from a talk I gave this past September at Strata Data NYC offering suggestions to companies...
85 days ago
The Practical Quant wrote a new blog post titled Vehicle-to-vehicle communication networks can help fuel smart cities
[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 sector.While some question whether V2X communication is necessary to get to fully autonomous...
97 days ago
The Practical Quant wrote a new blog post titled 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 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 and technologies, the main challenge is identifying and prioritizing use cases.As Artigas describes,...
111 days ago
The Practical Quant wrote a new blog post titled 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 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 of UC Berkeley’s AMPLab, which originated Apache Spark, Apache Mesos, and Alluxio.We began our...
125 days ago
The Practical Quant wrote a new blog post titled Effective mechanisms for searching the space of machine learning algorithms
[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 algorithms. In a recent survey article, Stanley went through the history of neuroevolution and listed...
139 days ago
The Practical Quant wrote a new blog post titled 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). 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 data science can be transformative (including improvements to decision-making or business operations,...
146 days ago
The Practical Quant wrote a new blog post titled 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). 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 data science can be transformative (including improvements to decision-making or business operations,...
146 days ago
The Practical Quant wrote a new blog post titled How Ray makes continuous learning accessible and easy to scale
[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Robert Nishihara and Philipp Moritz on a new framework for reinforcement learning and AI applications.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.In this episode of the Data Show, I spoke with Robert Nishihara and Philipp Moritz, graduate students at UC Berkeley and members of RISE Lab. I wanted to get an update on Ray, an open source distributed execution framework that...
153 days ago