Advice for emerging data scientists, the latest in model merging, and how GenAI can supercharge your creativity:  Host Jon Krohn gives us his highlights from a month of interviews, packed with tips from some of the leading names in data science and beyond. Guests include Daliana Liu, Charles Duhigg, Charles Goddard, Rosanne Liu and Andrey Kurenkov.

Additional materials: www.superdatascience.com/808

Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

The Super Data Science Podcast: Machine Learning | AI | Success

808: In Case You Missed It in July 2024

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 (https://go.aws/3zWS0au) and AWS Trainium (https://go.aws/3ycV6K0), by Babbel (https://www.babbel.com/superdata), the science-backed language-learning platform, and by Gurobi (https://www.gurobi.com/personas/optimization-for-data-scientists), the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com 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

815: Polars: Faster DataFrame Ops, with Marco Gorelli

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 natalie@superdatascience.com for sponsorship information.

816: Explaining AGI to a 94-Year-Old

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 (https://www.gurobi.com/personas/optimization-for-data-scientists/), the Decision Intelligence Leader, and by ODSC (https://odsc.com/california), the Open Data Science Conference. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com 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

817: The Positron IDE, Tidy NLP and MLOps with Dr. Julia Silge

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 natalie@superdatascience.com for sponsorship information.

818: In Case You Missed It in August 2024

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 (https://go.aws/3zWS0au) and AWS Trainium (https://go.aws/3ycV6K0), and by Gurobi (https://www.gurobi.com/personas/optimization-for-data-scientists), the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com 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

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

Jon Krohn takes OpenAI’s new models (o1-preview and o1-mini) for a spin in this Five-Minute Friday, learning their key strengths and limitations, and how the o1 series may represent yet another landmark for generative AI.

Additional materials: www.superdatascience.com/820

Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

820: OpenAI's o1 "Strawberry" Models

Llama 3.2 brings a new era of AI innovation with lightweight models tailored for on-device applications and powerful vision models for handling complex image inputs. Host Jon Krohn explores how this release pushes the boundaries of open-source AI, making it more accessible and versatile for developers. He also covers the Llama Stack toolkit, designed to streamline deployment, and Llama Guard 3, Meta’s latest content moderation solution. With extensive support from major cloud and hardware partners, Llama 3.2 is set to unlock groundbreaking possibilities for AI across mobile and beyond. Tune in to hear more.

Additional materials: www.superdatascience.com/824

Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

824: Llama 3.2: Open-Source Edge and Multimodal LLMs

The Super Data Science Podcast has moved! But, have no fear: We’re still publishing new episodes every single Tuesday and Friday.

You’ll find “The Super Data Science: ML & AI Podcast with Jon Krohn” via any major podcast-streaming app. Or if you like to watch podcasts, you can subscribe to our YouTube channel, where we have a special video version of the show: https://www.youtube.com/@SuperDataScienceWithJonKrohn

If you’d simply like to listen to the show on the web — while also getting convenient access to the episode transcript, show notes and other useful resources — you can point your browser to https://superdatascience.com/podcast. 

Thanks again for all of your support for the SuperDataScience Podcast over the years! We’re so grateful to have you listening and I can’t wait for you to subscribe and tune in.

Super Data Science Podcast Update

"Dive into the world of data visualization! This podcast explores why R's ggplot2 offers superior capabilities for statistical graphics, standing out with its elegant Grammar of Graphics. Discover how R provides consistent syntax, built-in statistical plots, and publication-ready output by default, contrasting with Python's more complex matplotlib and seaborn approaches for similar results. Tune in to understand why R remains the gold standard for statistical visualization and research publications."

R's Visualization Superiority: ggplot2 vs Matplotlib

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

New tracks tagged #Data Science Podcast