SuperDataScience

Anima Anandkumar joins us to discuss her work as a researcher in machine learning at NVIDIA and a professor at CalTech, and how they often go hand-in-hand and inform each other. In this episode you will learn: • Anima’s recent discovery of yoga [5:20] • How does Anima balance her work? [12:25] • Applications of Anima’s work [14:45] • Tensors [22:55] • Anima’s favorite NVIDIA projects [35:35] • What tools does NVIDIA use? [41:55] • CalTech interdisciplinary science [47:41] • The path to generalized artificial intelligence [57:19] • The skills to have to get into this field [1:00:27] • LinkedIn questions for Anima [1:07:03] Additional materials: www.superdatascience.com/473

In this episode, I share a note I received from a student who expressed his thoughts on the learning that never stops as he goes through his data science career. Additional materials: www.superdatascience.com/472

Kirill Eremenko returns to the SDS podcast as a guest to debunk common myths you may believe about getting a data science job. In this episode you will learn: • What has Kirill been up to? [3:48] • The genesis of the 99-days challenge [5:27] • 5 myths about pursuing a data science career [15:49] • First data science jobs [1:00:53] • 5 components for success [1:08:19] Additional materials: www.superdatascience.com/471

In this episode, I follow up on the popular book recommendation portion of the podcast with my own list of favorite books. Additional materials: www.superdatascience.com/470

Konrad Körding joins us to discuss his work in educating the next generation in deep learning and his views on the importance of causality in deep learning research. In this episode you will learn: • Konrad’s academic background [3:54] • Neuromatch Academy [5:23] • Artificial general intelligence [35:02] • Defining deep learning [41:24] • Symbol representation [44:12] • Konrad’s career journey [47:25] • What other skills should you develop for the future? [52:46] • What is the future of intelligence in our timeline? [56:37] Additional materials: www.superdatascience.com/469

In this episode, I tackle another historical topic: the history of data. Additional materials: www.superdatascience.com/468

Noah Gift joins us to discuss how he believes data science urgency and the end of hierarchies will change the world for the better. In this episode you will learn: • Catch up with Noah [2:50] • Educational options to pursue in data science [13:09] • Outside university education [24:06] • Noah as a prolific author [28:15] • Urgent applications of technology [37:34] • Noah’s income streams color code [48:38] • How to harness our free time to solve big problems [54:13] • Noah’s Coursera course [1:09:12] Additional materials: www.superdatascience.com/467

In this episode, I go over what separates a good data scientist from a great one in skills, practices, and approach. Additional materials: www.superdatascience.com/466

Konrad Kopczynski joins us to discuss how data, tracking, analytics, and key performance indicators can help your professional and personal development. In this episode you will learn: • What does Konrad do [3:40] • Tools and techniques used in Impakt Advisors [10:35] • Impakt’s unique hiring model [18:53] • How does Impakt manage remote work [21:36] • Konrad’s professional history and daily structure [28:42] • Konrad’s Iron Man triathlon [44:11] • Konrad’s years’ long project on presidential biographies [47:46] Additional materials: www.superdatascience.com/465

In this episode, I tackle three often conflated terms - AI, machine learning, and deep learning - to shine some light on what exactly they are. Additional materials: www.superdatascience.com/464

Matt Dancho joins us to discuss his various packages for time series analysis and his courses on the topic through his company Business Science. In this episode you will learn: • How Matt got into time series library development [4:22] • Business Science [7:00] • R Shiny [9:36] • Matt’s 6 time series models [14:11] • Timetk [15:02] • Modeltime [29:32] • Gluon package [36:04] • Modeltime Ensemble [43:12] • Modeltime H2O [45:22] • Modeltime Resample [48:10] Additional materials: www.superdatascience.com/463

In this episode, I discuss taking a positive approach to the good things that happen in life, rather than focusing on potential negative outcomes. Additional materials: www.superdatascience.com/462

Sam Hinton joins us to discuss his work since assisting COVID-19 data pipelines, now working in renewable energy and applications of ML and MLOps for the industry. In this episode you will learn: • Catching up with Sam [3:05] • Updates on the COVID-19 data pipelines [7:07] • Sam’s current work at Arenko [10:41] • Sam’s stint on Survivor, PhD, and his software engineering background [16:32] • Machine learning in renewable energy [35:23] • Sam’s day-to-day tools [49:33] • How can listeners utilize MLOps [53:08] • Sam’s forthcoming novel [59:05] Additional materials: www.superdatascience.com/461

In this episode, I talk about the ancient history of algebra, an important component of data science today. Additional materials: www.superdatascience.com/460

Vince Petaccio joins us to discuss how he sees data science, ML, and AI making positive impacts in the fight against climate change. In this episode you will learn: • Where in the world is Vince? [2:08] • Vince’s interest in climate science [4:33] • The Citizen’s Climate Lobby [9:12] • Where data science comes in [13:28] • Risks of relying on tools [31:54] • How can you make an impact? [37:28] Additional materials: www.superdatascience.com/459