How To Recession Proof Your Job - BONUS
Are you looking at all the layoffs and uncertainty going on and wondering if your company is the next to cut back?
Complexity Theory - ML 134
In today's episode, we speak with Neil Theise, a pathologist at NYU and author of Notes on Complexity: A Scientific Theory of Connection, Consciousness and Being. Expect to learn about complexity theory and its implications for sentience, how great ideas are formed, whether AGI can be built with silicon-based computers, and much more!
In today's episode we speak with Agata Checinska (Spotify) and Kasia Batko-Toluc (Citizen Network Watchdog Poland) about data privacy, accessibility, and accuracy. Expect to learn about how Poland approaches these sensitive topics, the power of deep fakes, and much more!
In today's episode we speak with Pierre Eliseeff, co-founder of Analyzr and causal inference expert. Expect to learn a 3-step blueprint for doing causal analysis, thinking critically about data, creating successful projects, and much more!
Data Visualization and Hugging Face - ML 131
In today's episode, we chat with Sylvain Lesage from Hugging Face, a specialist in data visualization and software engineering. Dive in to discover insights about Hugging Face's software engineering environment, invaluable data visualization techniques, and more!
Confidence as Data Scientist - ML 130
In today's episode, we chat with Adam Ross Nelson - a data scientist, career mentor, and writer. Our primary focus is understanding when you've achieved "good enough" skills. Additionally, we explore team dynamics, the importance of soft skills, and offer career guidance for budding data scientists.
A Case Study: Recommendation Engines - ML 129
In today's episode, we delve into a popular topic at Databricks: building recommendation engines. We'll guide you on how to plan such projects, measure your model's success, suggest effective algorithms, and cover many other insights!
Maximizing Efficiency in ML Project Development - ML 128
Ben and Michael delve into the world of data science and software development. They discuss the importance of setting standards and documentation in project development, the struggle of reviewing and maintaining code changes, and the need for programmatic solutions to automate review processes. They explore the journey of building prototypes, tackling uncertainties, and the quest for a more reliable and efficient review process.
AI that Make You Better - ML 127
In today's episode we speak with Paul Allen, the creator of Ancestry.com. Currently, he is CEO of Soar.com, a platform that leverages AI to make you live a more fulfilled and effective life. Expect to learn about applying LLMs to personal productivity, how Paul thinks about viral content, new applications for LLMs, and much more!
Challenges for LLM Implementation - ML 126
In today's episode, we speak with Anand Das, the CTO and co-founder of bito.ai, an LLM-powered code assistant. Expect to learn about managing LLM context, keeping LLMs up-to-date, common user pitfalls, and much more!
ML in the Cannabis Industry - ML 125
In today's episode, we speak with Shivek Sachdev, product owner at a seed-to-sale Cannabis company. Expect to learn about disrupting new industries, applying LLMs to daily work, and much more!
How AI Impacts Society - ML 124
In today's episode we speak to Eric Daimler, a White House Presidential Innovation Fellow, professor at Carnegie Mellon, and the current CEO of Conexus. Expect to learn about how AI is impacting the military, general workforce, and our understanding of sentience! Oh, and make sure you use farm animals when explaining technical concepts.
In today's episode, we speak with Jeff Procise, founder of Wintellect, an Azure-focused software consulting company. Expect to learn about your next LLM MVP on Azure, the societal impact of AI, the bifurcation of model size, and much more!
How to Create Team Utils - ML 122
Have you ever written code and thought, "hmm, I wonder if my teammates would use this." Well in today's episode, we show you how to go from concept to production-level code. Spoiler alert: you're going to have to write tests!
How to Get Sh*t Done - ML 121
In today's episode, Michael and Ben break down some surefire methods to be successful. If you follow these tips, you are guaranteed to co-found the next Google. Some topics include time boxing exciting work, tips for growing documentation, pitching to diverse crowds, and much more!