The 66th episode of Datacast is my conversation with Emeli Dral— the co-founder and CTO at Evidently AI, a startup developing tools to analyze and monitor the performance of machine learning models.

Our wide-ranging conversation touches on her educational background in Applied Mathematics and Computer Science; her work on recommendation systems and applied ML at Yandex; her popular teaching materials online and in-person; her startup on Industrial AI; her current journey with Evidently to tackle the model monitoring space, and much more.

Please enjoy my conversation with Emeli!

Listen to the show on (1) Spotify, (2) Apple Podcasts, (3)…

The 65th episode of Datacast is my conversation with David Sweet— an experienced quantitative trader and machine learning engineer who has used experimental methods to tune large-scale trading and recommendation systems.

Our wide-ranging conversation touches on his educational background in Physics and Ph.D. work on chaos theory; his work on open-source software and open content in the early 2000s; his Wall Street quant career dabbling across hedge-fund management, investment banking, and cryptocurrency trading; his work on recommendation systems at Instagram; his book “Tuning Up” that explores experimental optimization methods, and much more.

Please enjoy my conversation with David!

Listen…

The 64th episode of Datacast is my conversation with Fabiana Clemente — the Co-Founder and Chief Data Officer of YData, whose mission is to help companies and individuals to become the industry leaders by solving the true AI hidden secret — access to high-quality data.

Our wide-ranging conversation touches on her educational background in applied mathematics and data management, her time working as a developer building big data solutions, her foray into the data science universe, the genesis behind YData, synthetic data generation, differential privacy, model explainability, open-source as a strategy, and much more.

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Source: https://www.re-work.co/summits/virtual-ai-applications-summit-2021

Last month, I attended REWORK’s AI Applications Virtual Summit, which discovers machine learning tools and techniques to improve the financial, retail, and insurance experience. As a previous attendee of REWORK’s in-person summit, I have always enjoyed the unique mix of academia and industry, enabling attendees to meet with AI pioneers at the forefront of research and explore real-world case studies to discover the business value of AI.

In this long-form blog recap, I will dissect content from the talks that I found most useful from attending the summit. …

The 63rd episode of Datacast is my conversation with azin asgarian — an applied research scientist on Georgian’s R&D team, where she works with companies to help adopt applied research techniques to overcome business challenges.

Our wide-ranging conversation touches on her foray into studying math and computer science in Iran, her academic research on facial detection analysis at the University of Toronto, the benefits of being a teaching assistant, her interesting projects with Georgian Partners, real-world applications of transfer learning, and much more.

Listen to the show on (1) Spotify, (2) Apple Podcasts, (3) Google Podcasts, (4) TuneIn, (5)…

Source: https://www.applyconf.com/

Last week, I attended apply(), Tecton’s first-ever conference that brought together industry thought leaders and practitioners from over 30 organizations to share and discuss ML data engineering’s current and future state. The complexity of ML data engineering is the most significant barrier between most data teams and transforming their applications and user experiences with operational ML.

In this long-form blog recap, I will dissect content from 23 session and lightning talks that I found most useful from attending apply(). These talks cover everything from the rise of feature stores and the evolution of MLOps, to novel techniques and scalable platform…

The 62nd episode of Datacast is my conversation with Gordon Wong — a data modeling fanatic, data warehouse architect, and multi-hyper-growth startup veteran and team builder.

Our wide-ranging conversation touches on his foray into the database world, his interest in consulting, the evolution of data warehousing and business intelligence platforms, how to choose data tooling vendors, what it means to be data-driven, effective collaboration for data teams, data “hierarchy of needs”, data for social impact, and much more.

Listen to the show on (1) Spotify, (2) Apple Podcasts, (3) Google Podcasts, (4) TuneIn, (5) RadioPublic, (6) Stitcher, (7) Breaker

The 61st episode of Datacast is my chat with Louis Kirsch— a Ph.D. student at the Swiss AI Lab IDSIA, advised by Prof. Jürgen Schmidhuber.

We had a wide-ranging conversation covering his interest in programming growing up, his foray into AI research, the intersection of meta-learning and reinforcement-learning, contemporary challenges in AI, working with professor Schmidhuber, and much more.

Listen to the show on (1) Spotify, (2) Apple Podcasts, (3) Google Podcasts, (4) TuneIn, (5) RadioPublic, (6) Stitcher, and (7) iHeart Radio

Key Takeaways

Here are highlights from my conversation with Louis:

On Being A Self-Taught Programmer

I started programming when I was about 10. I…

Transform Sessions (Source: https://scale.com/events/transform)

A few weeks ago, I attended Transform, Scale AI’s first-ever conference that brought together an all-star line-up of the leading AI researchers and practitioners. The conference featured 19 sessions discussing the latest research breakthroughs and real-world impact across industries.

In this long-form blog recap, I will dissect content from the session talks that I found most useful from attending the conference. These talks cover everything from the future of ML frameworks and the importance of a data-centric mindset to AI applications at companies like Facebook and DoorDash. …

The 60th episode of Datacast is my interview with Dzejla Medjedovic— the Assistant Professor of Computer Science at the International University of Sarajevo and the author of “Algorithms and Data Structures for Massive Datasets.”

We had a wide-ranging conversation covering her foray into studying Computer Science, her Ph.D. in Applied Algorithms at Stony Brook University, her love for teaching, her industry internships at Microsoft, her Manning book, the tech scene in Sarajevo, and much more.

Listen to the show on (1) Spotify, (2) Apple Podcasts, (3) Google Podcasts, (4) TuneIn, (5) RadioPublic, (6) Stitcher, and (7) iHeart Radio

Key Takeaways

Here…

James Le

Data >< Product >< Community | https://jameskle.com/ | @le_james94

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