Super Data Science: ML & AI Podcast with Jon Krohn
Jon Krohn
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.
Episodes
Mentioned books
Oct 21, 2016 • 1h 7min
007: Advanced Analytics, Dynamic Simulations and Consulting World-wide with Artem Vladimirov
In this session of the Super Data Science Podcast, I chat with Top Analytics Consultant, Artem Vladimirov. You will learn about advanced analytics, get to know about what dynamic simulation is and learn some tips on how to get with data science.If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/7
Oct 16, 2016 • 54min
006: Financial Modeling and Data Science, Inputs vs Assumptions and Going Big with Xinran Liu
Expert Financial Modeler Xinran Liu discusses financial modeling, data science, inputs vs assumptions, and collaborations between the two fields. They dive into valuing companies, sensitivity analysis, the importance of assumptions, and distinctions between industry and consulting work.
Oct 9, 2016 • 1h 4min
005: Computer Forensics, Fraud Analytics And Knowing When To Take A Break With Dmitry Korneev
Forensics Investigator Dmitry Korneev discusses computer forensics and fraud analytics. They explore the challenges in fraud analytics in the high-tech world, advancements in natural language processing, analyzing fraud with Benford's Law, and insights from 'How Life Imitates Chairs' by Gary Kasparov.
Oct 2, 2016 • 1h 1min
004: Data and Strategy, Three Pillars of Research and Building your Career with Brendan Hogan
Business strategy expert Brendan Hogan shares insights on using data to alter business strategy, the three pillars of research, and building a successful career from strengths. Topics include leveraging customer data for business strategy, navigating career success in data science, and the significance of mentorship in professional development.
Sep 25, 2016 • 54min
003: Defining the Data Problem, Academia vs Career and R Modeling Libraries with Dr. Wilson Pok
Dr. Wilson Pok shares insights on transitioning from academia to data science, emphasizing clear problem definition, Bayesian analysis, and managing uncertainty. He discusses using data insights in business, conducting randomized control trials for marketing analysis, simplifying complex data models for stakeholders, and the importance of continuous monitoring and retraining to prevent model deterioration. Tools like R, Python, ggplot2, Carrot, and XGBoost are highlighted, along with the challenges faced by data scientists and the significance of data literacy.
Sep 14, 2016 • 51min
002: Machine Learning, Recommender Systems and The Future of Data with Hadelin de Ponteves
Machine learning expert Hadelin de Ponteves discusses transitioning from finance to data science, working at Google and Canal+, AI implications for data scientists, unconventional sleep routine for productivity, tools used in ML tasks, future job opportunities with the rise of technology, and book recommendations for future data scientists.
8 snips
Sep 10, 2016 • 42min
001: Self-serve Analytics, Data Science MBA and Managing a Team of Analysts with Ruben Kogel
Ruben Kogel, an experienced data analyst in the startup space, discusses self-serve analytics, managing a team of analysts, and transitioning from a chemistry background to data science at Udemy. Topics include AWS Redshift, data science wins at Udemy, and the excitement and challenges of being a data scientist.
