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Our popular course Introduction to QuantLib Development will be taking place June 18-20th, 2018.

 

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The Practical Quant wrote a new blog post titled What machine learning means for software development
[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 and layoffs, or will see programming evolve into something different—perhaps even something more...
6 days ago
The Practical Quant wrote a new blog post titled Data regulations and privacy discussions are still in the early stages
[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 trends in data privacy and growing interest in ethics among data professionals.Here are some...
12 days ago
The Practical Quant wrote a new blog post titled Managing risk in machine learning models
[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 organizations that are deploying machine learning.Some high-profile examples of models gone awry have raised...
12 days ago
The Practical Quant wrote a new blog post titled Understanding automation
[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 machine learning and AI tools that can be used to enable automation.Let me begin by citing a...
12 days ago
The Practical Quant wrote a new blog post titled The real value of data requires a holistic view of the end-to-end data pipeline
[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 artificial intelligence products at Verizon. I wanted his perspective on a range of issues, including...
12 days ago
The Practical Quant wrote a new blog post titled The evolution of data science, data engineering, and AI
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: A special episode to mark the 100th episode.This episode of the Data Showmarks our 100th episode. This podcast stemmed out of video interviews conducted at O’Reilly’s 2014 Foo Camp. We had a collection of friends who were key members of the data science and big data communities on hand and we decided to record short conversations with them. We originally conceived of using those initial conversations to be the basis of a regular series of video interviews. The logistics of studio interviews proved too...
54 days ago
The Practical Quant wrote a new blog post titled Companies in China are moving quickly to embrace AI technologies
[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Jason Dai on the first year of BigDL and AI in China.In this episode of the Data Show, I spoke with Jason Dai, CTO of Big Data Technologies at Intel, and one of my co-chairs for the AI Conference in Beijing. I wanted to check in on the status of BigDL, specifically how companies have been using this deep learning library on top of Apache Spark, and discuss some newly added features. It turns out there are quite a number of companies already using BigDL in production, and we talked about some of the popular...
68 days ago
The Practical Quant wrote a new blog post titled How to build analytic products in an age when data privacy has become critical
[A version of this post appears on the O'Reilly Radar.]Privacy-preserving analytics is not only possible, but with GDPR about to come online, it will become necessary to incorporate privacy in your data products.In this post, I share slides and notes from a talk I gave in March 2018 at the Strata Data Conference in California, offering suggestions for how companies may want to build analytic products in an age when data privacy has become critical. A lot has changed since I gave this presentation: numerous articles have been written about Facebook’s privacy policies, its CEO...
75 days ago
The Practical Quant wrote a new blog post titled Teaching and implementing data science and AI in the enterprise
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Jerry Overton on organizing data teams, agile experimentation, and the importance of ethics in data science.In this episode of the Data Show, I spoke with Jerry Overton, senior principal and distinguished technologist at DXC Technology. I wanted the perspective of someone who works across industries and with a variety of companies. I specifically wanted to explore the current state of data science and AI within companies and public sector agencies. As much as we talk about use cases, technologies, and...
82 days ago
The Practical Quant wrote a new blog post titled Building tools for the AI applications of tomorrow
[A version of this post appears on the O'Reilly Radar.]We’re currently laying the foundation for future generations of AI applications, but we aren’t there yet.By Ben Lorica and Mike LoukidesFor the last few years, AI has been almost synonymous with deep learning (DL). We’ve seen AlphaGo touted as an example of deep learning. We’ve seen deep learning used for naming paint colors (not very successfully), imitating Rembrandt and other great painters, and many other applications. Deep learning has been successful in part because, as François Chollet tweeted, “you can achieve a surprising amount...
82 days ago
The Practical Quant wrote a new blog post titled The importance of transparency and user control in machine learning
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Guillaume Chaslot on bias and extremism in content recommendations.In this episode of the Data Show, I spoke with Guillaume Chaslot, an ex-YouTube engineer and founder of AlgoTransparency, an organization dedicated to helping the public understand the profound impact algorithms have on our lives. We live in an age when many of our interactions with companies and services are governed by algorithms. At a time when their impact continues to grow, there are many settings where these algorithms are far from...
95 days ago
The Practical Quant wrote a new blog post titled What machine learning engineers need to know
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Jesse Anderson and Paco Nathan on organizing data teams and next-generation messaging with Apache Pulsar.In this episode of the Data Show, I spoke Jesse Anderson, managing director of the Big Data Institute, and my colleague Paco Nathan, who recently became co-chair of Jupytercon. This conversation grew out of a recent email thread the three of us had on machine learning engineers, a new job role that LinkedIn recently pegged as the fastest growing job in the U.S. In our email discussion, there was some...
110 days ago
The Practical Quant wrote a new blog post titled How to train and deploy deep learning at scale
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Ameet Talwalkar on large-scale machine learning.In this episode of the Data Show, I spoke with Ameet Talwalkar, assistant professor of machine learning at CMU and co-founder of Determined AI. He was an early and key contributor to Spark MLlib and a member of AMPLab. Most recently, he helped conceive and organize the first edition of SysML, a new academic conference at the intersection of systems and machine learning (ML).We discussed using and deploying deep learning at scale. This is an empirical era for...
124 days ago
The Practical Quant wrote a new blog post titled Using machine learning to monitor and optimize chatbots
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Ofer Ronen on the current state of chatbots.In this episode of the Data Show, I spoke with Ofer Ronen, GM of Chatbase, a startup housed within Google’s Area 120. With tools for building chatbots becoming accessible, conversational interfaces are becoming more prevalent. As Ronen highlights in our conversation, chatbots are already enabling companies to automate many routine tasks (mainly in customer interaction). We are still in the early days of chatbots, but if current trends persist, we’ll see bots...
133 days ago
The Practical Quant wrote a new blog post titled Unleashing the potential of reinforcement learning
[A version of they post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Danny Lange on how reinforcement learning can accelerate software development and how it can be democratized.In this episode of the Data Show, I spoke with Danny Lange, VP of AI and machine learning at Unity Technologies. Lange previously led data and machine learning teams at Microsoft, Amazon, and Uber, where his teams were responsible for building data science tools used by other developers and analysts within those companies. When I first heard that he was moving to Unity, I was curious as to why he...
138 days ago
The Practical Quant wrote a new blog post titled Graphs as the front end for machine learning
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Leo Meyerovich on building large-scale, interactive applications that enable visual investigations.In this episode of the Data Show, I spoke with Leo Meyerovich, co-founder and CEO of Graphistry. Graphs have always been part of the big data revolution (think of the large graphs generated by the early social media startups). In recent months, I’ve come across companies releasing and using new tools for creating, storing, and (most importantly) analyzing large graphs. There are many problems and use cases...
152 days ago
The Practical Quant wrote a new blog post titled Machine learning needs machine teaching
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Mark Hammond on applications of reinforcement learning to manufacturing and industrial automation.In this episode of the Data Show, I spoke with Mark Hammond, founder and CEO of Bonsai, a startup at the forefront of developing AI systems in industrial settings. While many articles have been written about developments in computer vision, speech recognition, and autonomous vehicles, I’m particularly excited about near-term applications of AI to manufacturing, robotics, and industrial automation. In a recent...
166 days ago
The Practical Quant wrote a new blog post titled Introducing RLlib: A composable and scalable reinforcement learning library
[A version of this post appears on the O'Reilly Radar.]RISE Lab’s Ray platform adds libraries for reinforcement learning and hyperparameter tuning.In a previous post, I outlined emerging applications of reinforcement learning (RL) in industry. I began by listing a few challenges facing anyone wanting to apply RL, including the need for large amounts of data, and the difficulty of reproducing research results and deriving the error estimates needed for mission-critical applications. Nevertheless, the success of RL in certain domains has been the subject of much media coverage. This has sparked...
179 days ago
The Practical Quant wrote a new blog post titled How machine learning can be used to write more secure computer programs
[A version of this post appears on the O'Reilly Radar.]The O’Reilly Data Show Podcast: Fabian Yamaguchi on the potential of using large-scale analytics on graph representations of code.In this episode of the Data Show, I spoke with Fabian Yamaguchi, chief scientist at ShiftLeft. His 2015 Ph.D. dissertation sketched out how the combination of static analysis, graph mining, and machine learning, can be used to develop tools to augment security analysts. In a recent post, I argued for machine learning tools to augment teams responsible for deploying and managing models in production (machine...
180 days ago
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...
187 days ago