Superdatascience

This week, Sarah Catanzaro, General Partner at Amplify Partners joins Jon for an episode that dives into the venture capital side of data science. Learn how to fund your data science business idea, take note of what start-ups can do to survive or raise capital in the current economic climate, and discover how to break into the field of venture capital yourself. In this episode you will learn: • Angel vs. venture capital vs. private equity investment [7:27] • How early-stage investment is made prior to a firm having product-market fit [14:33] • How to pick winners in early-stage investments [28:08] • Tricks to accelerating from a data science idea to obtaining funding [36:21] • Observational causal inference [44:01] • How to get involved in venture capital [47:37] Additional materials: www.superdatascience.com/601

Rest and relaxation await as Steve Fazzari joins us this week for a special edition of the podcast! Tune in for a rejuvenating session of Yoga Nidra led beautifully by the expert. Additional materials: www.superdatascience.com/600

This week, Mikiko Bazeley, Senior Software Engineer at Mailchimp joins the podcast to share her in-depth knowledge of MLOps: Machine Learning Operations. Tune in to hear her discuss what it entails, why it's so critical for the efficiency of any data science team, and the most important tools you need to master for career success in this field. In this episode you will learn: • What MLOps is [11:40] • Mikiko’s role at Mailchimp and why MLOps is critical for the efficiency of any data science team [27:11] • The three most important MLOps tools [32:15] • The six most essential MLOps skills for data scientists [47:01] • The key factors Mikiko looks when hiring engineers [1:07:31] • Mikiko’s productivity tricks for balancing software engineering, content creation, and her athletic pursuits [1:13:20] Additional materials: www.superdatascience.com/599

Ben Taylor makes a fourth appearance on Five-Minute Friday to discuss the best ways to introduce STEM to children. Tune in to hear the many ways in which he thinks STEM education will evolve in the future. Additional materials: www.superdatascience.com/598

Dr. Miles Brundage, Head of Policy Research at OpenAI, joins Jon Krohn this week to discuss AI model production, policy, safety, and alignment. Tune in to hear him speak on GPT-3, DALL-E, Codex, and CLIP as well. In this episode you will learn: • Miles’ role as Head of Policy Research at OpenAI [4:35] • OpenAI's DALL-E model [7:20] • OpenAI's natural language model GPT-3 [30:43] • OpenAI's automated software-writing model Codex [36:57] • OpenAI’s CLIP model [44:01] • What sets AI policy, AI safety, and AI alignment apart from each other [1:07:03] • How A.I. will likely augment more professions than it displaces them [1:12:06] Additional materials: www.superdatascience.com/597

Ben Taylor returns for a third Five-Minute Friday episode! This week, he looks ahead and digs into what we can expect from the A.I. platforms of the future. Additional materials: www.superdatascience.com/596

Tune in as Joe Reis and Matt Housley, co-founders of Ternary Data and co-authors of the book “Fundamentals of Data Engineering” join Jon Krohn to discuss major undercurrents across the data engineering lifecycle, and their top tools and techniques. In this episode you will learn: • What is data engineering? [3:55] • Why Joe and Matt identify as “recovering data scientists” [6:12] • What kinds of people tend to become data scientists vs. data engineers [10:38]? • Key components of Joe and Matt’s book [26:31] • Major undercurrents across the data engineering lifecycle [28:26] • The most under-utilized tool in a data engineer's toolbox [34:39] • How there are tradeoffs in any data pipeline latency considerations, but faster is typically the default assumption [38:55] • Joe and Matt’s favorite data engineering tools and techniques [43:39] Additional materials: www.superdatascience.com/595

This week, Jon Krohn and A.I. industry veteran Ben Taylor discuss the driving factors that push CEOs to prioritize A.I. over other technologies. Additional materials: www.superdatascience.com/594

Jon welcomes Professor Philip Bourne, Founding Dean of the School of Data Science at the University of Virginia to discuss his biomedical data science research, the importance of open-source and open-access within the industry and the data science skills you need to succeed today. In this episode you will learn: • Why Philip founded a School of Data Science [6:08] • How computing and data science have evolved across academic departments [15:55] • The improvements needed in higher education [26:44] • The most important data science skills for academia and industry and the 4+1 model [36:49] • Philip’s biomedical data science research and its fascinating practical applications [43:24] • The essential roles of open-source code and open-access publishing in data science [1:01:27] Additional materials: www.superdatascience.com/593

In this episode, Jon Krohn welcomes A.I. industry veteran Ben Taylor to discuss how to sell multimillion dollar A.I. contracts. Tune in to hear why trust and proof of value are some of the critical steps in his sales process. Additional materials: www.superdatascience.com/592

Mars Buttfield-Addison, PhD Candidate at the University of Tasmania, joins Jon Krohn for a high-energy episode covering everything from Machine Learning simulations to Swift, space junk, and more! In this episode you will learn: • What simulations and synthetic data are, and why they can be invaluable for real-life applications [5:47] • How simulated bots can solve any problem [9:07] • Practical uses of simulated data [21:49] • Why the mobile operating system language Swift is interesting for A.I. [25:46] • Why it's critical to track the amount of junk in space [35:47] • Whether programming or statistical skills are more important in data science [47:05] • What it’s like creating video games in a "secret" games lab [56:45] • Why you might want to do a data science internship in industry before pursuing in academia [ 1:01:54] Additional materials: www.superdatascience.com/591

In this episode, Jon continues his two-part series on artificial general intelligence (AGI) and why we are unlikely to realize it anytime soon. Listen in as Jon reviews Meta's Yann LeCun's seven-part perspective on the topic. Additional materials: www.superdatascience.com/590

Hilary Mason, Co-Founder and CEO of Hidden Door, joins Jon Krohn for a live discussion that explores narrative A.I., emerging ML techniques, and how her OSEMN data science process developed. In this episode you will learn: How narrative A.I. can assist creativity [5:14] How to build ML products that have no quantitative error function to optimize [10:31] How to ensure creative A.I. systems do not output non-sense or explicit content [16:58] Hilary's OSEMN data science process [21:05] The emerging ML technique she’s most excited about [24:58] What it takes to be successful as CEO of an early-stage A.I. company [27:20] What she looks for in engineering hires [32:28] How she’s hopeful A.I. will transform our lives for the better in the decades to come [38:48] Additional materials: www.superdatascience.com/589

In this episode, Jon kicks off a two-part series that sees him explore the popular topic of artificial general intelligence and why it might–or might not–be only a few years away. Listen in as Jon explains the several reasons why he doesn't believe that AGI is nigh. Additional materials: www.superdatascience.com/588

Mark Freeman, Senior Data Scientist at Humu, joins Jon Krohn to talk about all things data engineering and offers listeners some critical tips for their data science career journey – from what it takes to get promoted to his number one tip for getting hired at a fast-growing capital-backed startup. In this episode you will learn: How Humu leverages data and machine learning to improve workplace behaviors [10:38] What is data engineering? [14:21] What it takes to get promoted into more senior data science roles [20:55] The differences between junior, senior, and staff data scientists [30:21] Mark’s top tools for data extraction, modeling, and pipeline engineering [37:08] Mark’s number one tip for getting hired at a fast-growing venture capital-backed startup [53:10] Why all data scientists should be interested in Web3 [1:11:53] Additional materials: www.superdatascience.com/587

In this episode, Jon dives into the popular topic of social media and its impact on his productivity. Tune in to hear how minimizing the use of social media can positively impact your days, mental health and work. Additional materials: www.superdatascience.com/586

In this episode, Dr. Thomas Wiecki, Core Developer of the PyMC Library and CEO of PyMC Labs, joins Jon for a masterclass in Bayesian statistics. Tune in to hear about PyMC, and discover why Bayesian statistics can be more powerful and interpretable than any other data modeling approach. In this episode you will learn: What Bayesian statistics is [7:30] Why Bayesian statistics can be more powerful and interpretable than any other data modeling approach [17:20] How PyMC was developed [20:41] Commercial applications of Bayesian stats [43:07] How to build a successful company culture [1:03:14] What Thomas looks for when hiring [1:11:13] Thomas’s top resources for learning Bayesian stats yourself [1:13:57] Additional materials: www.superdatascience.com/585

In this episode, Jon reviews the remarkable natural language model Codex by OpenAI. Learn why it has amassed a waitlist and how you can leverage its practical applications in your work. Additional materials: www.superdatascience.com/584

In this episode, natural language processing (NLP) expert and Lead Data Scientist at CB Insights, Rongyao Huang, joins Jon Krohn to discuss NLP. Listen in for a thorough review of the field over the past decade and how the coming iron age of NLP will help us overcome the limitations of today's approaches. In this episode you will learn: The evolution of NLP techniques over the past decade [4:14] What's next in the coming iron age of NLP [35:33] Rongyao’s Bauhaus-inspired model for effective data science [43:12] Rongyao's long-term career pathfinding framework [51:50] Rongyao’s top tips for staying sane while juggling career and family [1:00:30] Additional materials: www.superdatascience.com/583

In this episode, Jon wraps up his three-part series on business value and machine learning. Listen in as he explains why starting with simple models is best, and why speed is likely more important to your users than accuracy. Additional materials: www.superdatascience.com/582