819: PyTorch: From Zero to Hero, with Luka Anicin

SuperDataScience veteran and Udemy teacher Luka Anicin is on the podcast to talk about his brand-new course, “PyTorch: From Zero to Hero”, available exclusively on superdatascience.com. Host Jon Krohn asks Luka why he feels that every data scientist should consider PyTorch as their default Python library, and why “keeping it simple” can secure the success of a machine learning project. This episode is brought to you by AWS Inferentia and AWS Trainium, and by Gurobi, the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: • About the PyTorch library [03:29] • Why PyTorch became so popular [25:24] • How to increase accuracy and efficiency in PyTorch [31:49] • How to utilize transfer learning [35:44] • Why real-world projects are essential to data scientists [41:10] • About Datablooz [46:49] Additional materials: www.superdatascience.com/819

Experts from AI and data science discuss the impact and benefits of decentralization, the importance of structuring AI systems in business, and why knowing the basics will always matter for data engineers. Listen to Shingai Manjengwa (episode 809), Daniel Hulme (episode 807), Jerry Yurchisin (episode 813) and Nick Elprin (episode 811) explore a future world of work that rewards continuing learners, sets tasks for the people best suited to complete them rather than those whose job titles reflect the spec, and applies a fleet of ‘AI agents’ to solve complex business tasks. Additional materials: www.superdatascience.com/818  Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

Dr. Julia Silge, Engineering Manager at Posit, introduces the brand-new Positron IDE, perfect for exploratory data analysis and visualization. She also lays out her top picks for LLMs that boost coding efficiency and discusses when traditional NLP methods might be the smarter choice over LLMs. Plus, Julia highlights some must-know open-source libraries that make managing MLOps easier than ever. Tune in for insights that every data scientist, ML engineer, and developer will find useful. This episode is brought to you by Gurobi, the Decision Intelligence Leader, and by ODSC, the Open Data Science Conference. Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: • Overview of Posit and Positron IDE [05:20] • How the needs of a data scientist differ from those of a software developer [10:54] • How to contribute to the open-source Positron [19:50] • MLOps and Vetiver: Tools for deploying and maintaining ML models [37:01] • Natural Language Processing (NLP) and the Tidyverse approach [50:34] • The role of AI and LLMs in data science education [1:24:18] Additional materials: www.superdatascience.com/817

Jon Krohn takes on a listener's challenge to explain his work in data science to his 94-year-old grandmother, Annie. This heartwarming conversation covers what data is, the role of a data scientist, and breaks down artificial intelligence (AI) and artificial general intelligence (AGI) in simple terms. The episode provides a fresh take on how to communicate complex topics to a lay audience, offering both clarity and insight. Additional materials: www.superdatascience.com/816  Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

Polars, Python, Narwhals, Rust, and Pandas: Marco Gorelli talks to Jon Krohn about the many ways to use the newest data libraries available, the joys of open-source development, and the best method to win prizes in forecasting competitions. This episode is brought to you by AWS Inferentia and AWS Trainium, by Babbel, the science-backed language-learning platform, and by Gurobi, the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: • When to use Polars vs Pandas [08:26] • How Polars optimizes string operations and data processing [20:08] • Where Narwhals outstrips Polars and Pandas [48:37] • The benefits of using Altair [55:21] • Addressing the lack of women in data science [1:09:58] • How to win a forecasting competition [1:16:58] Additional materials: www.superdatascience.com/815

As summer winds down, this episode shifts focus from the usual tech discussions to something more personal: reflecting on the importance of balancing work with life’s simple pleasures. While the world of data science and AI continues to evolve rapidly, it's essential to remember that true success isn't just about professional milestones. It’s also about cherishing the moments that make life meaningful. Tune in for a brief but impactful reflection on how to redefine success to include not just achievements, but also the everyday joys that often go unnoticed. Additional materials: www.superdatascience.com/814  Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

Jerry Yurchisin from Gurobi joins Jon Krohn to break down mathematical optimization, showing why it often outshines machine learning for real-world challenges. Find out how innovations like NVIDIA’s latest CPUs are speeding up solutions to problems like the Traveling Salesman in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: • The Burrito Optimization Game and mathematical optimization use cases [03:36] • Key differences between machine learning and mathematical optimization [05:45] • How mathematical optimization is ideal for real-world constraints [13:50] • Gurobi’s APIs and the ease of integrating them [21:33] • How LLMs like GPT-4 can help with optimization problems [39:39] • Why integer variables are so complex to model [01:02:37] • NP-hard problems [01:11:01] • The history of optimization and its early applications [01:26:23] Additional materials: www.superdatascience.com/813

In this episode of Five-Minute Friday, Jon Krohn investigates published findings from the startup Sakana AI and its paper’s co-authors from the University of Oxford, the University of British Columbia and the Vector Institute in Toronto. These authors explore the potential of The AI Scientist, a framework that could change the way we conduct scientific research forever. Additional materials: www.superdatascience.com/812  Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

Nick Elprin talks to Jon Krohn about how and when to scale a data science team and its workflows to secure a company’s commercial viability. You’ll also hear how to launch your own data science startup and why it’s so important to understand that AI tools are not one-size-fits-all. This episode is brought to you by AWS Inferentia and AWS Trainium. Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: • How Nick served enterprises with his AI startup, Domino Data Lab [05:36] • About the Navy’s own mine detection models [17:43] • The hype surrounding GenAI [30:35] • How AI platforms integrate with business strategies [39:49] • When it’s time to integrate an AI tool into your business [51:12] • Why Nick started Domino Data Lab [1:03:53] Additional materials: www.superdatascience.com/811

Self-driving cars are here, and Jon Krohn is breaking down the five levels of automation that could change driving forever. From full human control at Level 0 to cars that drive themselves in any condition at Level 5, get the real story on what these levels mean. With firsthand insights from a recent autonomous vehicle experience, this episode cuts through the buzz and tells you what’s coming next. Additional materials: www.superdatascience.com/810  Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.