Predictive Maintenance Using Deep Learning and Reliability Engineering with Shayan Mortazavi - #540

Predictive Maintenance Using Deep Learning and Reliability Engineering with Shayan Mortazavi - #540

Today we’re joined by Shayan Mortazavi, a data science manager at Accenture. In our conversation with Shayan, we discuss his talk from the recent SigOpt HPC & AI Summit, titled A Novel Framework Predictive Maintenance Using Dl and Reliability Engineering. In the talk, Shayan proposes a novel deep learning-based approach for prognosis prediction of oil and gas plant equipment in an effort to prevent critical damage or failure. We explore the evolution of reliability engineering, the decision to use a residual-based approach rather than traditional anomaly detection to determine when an anomaly was happening, the challenges of using LSTMs when building these models, the amount of human labeling required to build the models, and much more! The complete show notes for this episode can be found at twimlai.com/go/540

Avsnitt(777)

Machine Learning to Discover Physics and Engineering Principles with Nathan Kutz - TWiML Talk #162

Machine Learning to Discover Physics and Engineering Principles with Nathan Kutz - TWiML Talk #162

In this episode, I’m joined by Nathan Kutz, Professor of applied mathematics, electrical engineering and physics at the University of Washington to discuss his research into the use of machine learning to help discover the fundamental governing equations for physical and engineering systems from time series measurements. For complete show notes visit twimlai.com/talk/162

9 Juli 201843min

Automating Complex Internal Processes w/ AI with Alexander Chukovski - TWiML Talk #161

Automating Complex Internal Processes w/ AI with Alexander Chukovski - TWiML Talk #161

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

5 Juli 201839min

Designing Better Sequence Models with RNNs with Adji Bousso Dieng - TWiML Talk #160

Designing Better Sequence Models with RNNs with Adji Bousso Dieng - TWiML Talk #160

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.

2 Juli 201838min

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

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