The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.

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Love Love: AI and ML in Tennis with Stephanie Kovalchik - TWiML Talk #159

Love Love: AI and ML in Tennis with Stephanie Kovalchik - TWiML Talk #159

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.

29 Juni 201846min

Growth Hacking Sports w/ Machine Learning with Noah Gift - TWiML Talk #158

Growth Hacking Sports w/ Machine Learning with Noah Gift - TWiML Talk #158

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

28 Juni 201850min

Fine-Grained Player Prediction in Sports with Jennifer Hobbs - TWiML Talk #157

Fine-Grained Player Prediction in Sports with Jennifer Hobbs - TWiML Talk #157

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

27 Juni 201842min

Targeted Ticket Sales Using Azure ML with the Trail Blazers w/ Mike Schumacher & Chenhui Hu - TWiML Talk #156

Targeted Ticket Sales Using Azure ML with the Trail Blazers w/ Mike Schumacher & Chenhui Hu - TWiML Talk #156

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.

26 Juni 201837min

AI for Athlete Optimization with Sinead Flahive - TWiML Talk #155

AI for Athlete Optimization with Sinead Flahive - TWiML Talk #155

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!

25 Juni 201840min

Omni-Channel Customer Experiences with Vince Jeffs - TWiML Talk #154

Omni-Channel Customer Experiences with Vince Jeffs - TWiML Talk #154

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.

21 Juni 201843min

Workforce Intelligence for Automation & Productivity with Michael Kempe - TWiML Talk #153

Workforce Intelligence for Automation & Productivity with Michael Kempe - TWiML Talk #153

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.

20 Juni 201836min

Data Platforms for Decision Automation at Scotiabank with Jim Saleh - TWiML Talk #152

Data Platforms for Decision Automation at Scotiabank with Jim Saleh - TWiML Talk #152

In this show, part of our PegaWorld 18 series, I'm joined by Jim Saleh, Senior Director of process and decision automation at Scotiabank. Jim is tasked with helping the bank transition from a world where customer interactions are based on historical analytics to one where they’re based on real-time decisioning and automation. In our conversation we discuss what’s required to deliver real-time decisioning, starting from the ground up with the data platform. In this vein we explore topics like data lakes, data warehouses, integration, and more, and the effort required to take advantage of these. The notes for this show can be found at twimlai.com/talk/152. For more info on our PegaWorld 2018 series, visit twimlai.com/pegaworld2018.

19 Juni 201832min

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