In this episode, I'm joined by Alexander Chukovski, Director of Data Services at Munich, Germany based career platform, Experteer. In our conversation, we explore Alex’s journey to implement machine learning at Experteer, the Experteer NLP pipeline and how it’s evolved, Alex’s work with deep learning based ML models, including models like VDCNN and Facebook’s FastText offering and a few recent papers that look at transfer learning for NLP.

Check out the complete show notes at twimlai.com/talk/161

In this episode, I'm joined by Adji Bousso Dieng, PhD Student in the Department of Statistics at Columbia University to discuss two of her recent papers, “Noisin: Unbiased Regularization for Recurrent Neural Networks” and “TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency.” We dive into the details behind both of these papers and learn a ton along the way.

In the final show in our AI in Sports series, I’m joined by Stephanie Kovalchik, Research Fellow at Victoria University and Senior Sports Scientist at Tennis Australia. In our conversation we discuss Tennis Australia's use of data to develop a player rating system based on ability and probability, some of the interesting products her Game Insight Group is developing, including a win forecasting algorithm, and a statistic that measures a given player’s workload during a match.

In the final show in our AI in Sports series, I’m joined by Stephanie Kovalchik, Research Fellow at Victoria University and Senior Sports Scientist at Tennis Australia. In our conversation we discuss Tennis Australia's use of data to develop a player rating system based on ability and probability, some of the interesting products her Game Insight Group is developing, including a win forecasting algorithm, and a statistic that measures a given player’s workload during a match.

In this episode of our AI in Sports series I'm joined by Noah Gift, Founder and Consulting CTO at Pragmatic Labs and professor at UC Davis. Noah and I discuss some of his recent work in using social media to predict which players hold the most on-court value, and how this work could lead to more complete approaches to player valuation.

Check out the show notes at twimlai.com/talk/158

In this episode of our AI in Sports series, I'm joined by Jennifer Hobbs, Senior Data Scientist at STATS, a collector and distributor of sports data, to discuss the STATS data pipeline and how they collect and store different types of data for easy consumption and application. We also look into a paper she co-authored, Mythbusting Set-Pieces in Soccer, which was presented at the MIT Sloan Conference this year.

https://twimlai.com/talk/157

In today’s episode of our AI in Sports series I'm joined by Mike Schumacher, director of business analytics for the Portland Trail Blazers, and Chenhui Hu, a data scientist at Microsoft to discuss how the Blazers are using machine learning to produce better-targeted sales campaigns, for both single-game and season-ticket buyers.

This week we’re excited to kick off a series of shows on AI in sports. In this episode I'm joined by Sinead Flahive, data scientist at Dublin, Ireland based Kitman Labs to discuss Kitman’s Athlete Optimization System, which allows sports trainers and coaches to collect and analyze data for player performance optimization and injury reduction. Enjoy!

In this, the final episode of our PegaWorld series I’m joined by Vince Jeffs, Senior Director of Product Strategy for AI and Decisioning at Pegasystems. Vince and I had a great talk about the role AI and advanced analytics will play in defining future customer experiences. We do this in the context provided by one of his presentations from the conference, which explores four technology scenarios from Pegasystems’ innovation labs. These look at a connected car experience, the use of deep learning for diagnostics, dynamic notifications, and continuously optimized marketing. We also get into an interesting discussion about how much is too much when it comes to hyperpersonalized experiences, and how businesses can manage this challenge. The notes for this show can be found at twimlai.com/talk/154. For more information on the Pegaworld series, visit twimlai.com/pegaworld2018.

In this episode of our PegaWorld series, I’m joined by Michael Kempe, chief operating officer at global share registry and financial services provider Link Market Services. In the interview, Michael and I dig into Link’s use of workforce intelligence software to allow it to track and analyze the performance of its workforce and business processes. Michael and I discuss some of the initial challenges associated with implementing this type of system, including skepticism amongst employees, and how it ultimately sets the stage for the Link’s broader use of machine learning, AI and so called “robotic process automation” to increase workforce productivity. The notes for this show can be found at twimlai.com/talk/153. For more information on our PegaWorld series, visit twimlai.com/pegaworld2018.