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 time...
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...
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:...
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]...
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
In this week’s episode, I take you behind the scenes of our video tutorial productions to see what goes into making our tutorials. Additional materials: www.superdatascience.com/458
Harpreet Sahota joins us to discuss his data science mentorship work outside his day job and how you can land your dream job. In this episode you will learn: Harpreet’s current life and location [2:25] Data Community Content Creator Awards [8:37] The Artists of Data Science Podcast [14:46] Data Science Dream Job [24:18] Harpreet’s day job at Price Industries [30:48] Coming in data science from a non-data background [40:55] Tools and skills to know [47:57] Additional materials: www.superdatascien...
In this week’s episode, I talk about one of my favorite time management techniques: the Pomodoro technique. Additional materials: www.superdatascience.com/456
Horace Wu joins us to discuss his work on Syntheia, a unique product that helps sift through massive amounts of legal data to augment the capacities and function of law firms. In this episode you will learn: Horace’s life and work in New York City [5:00] Syntheia and Horace’s role there [6:25] Horace’s background [12:07] Nearmap [16:35] Syntheia NLP use cases [21:46] Design, coding, and the team [34:19] What skills does one need for this field? [41:41] What would Horace do differently and what i...
In this episode, I continue my discussion about the quick-paced growth of technology and how it impacts different fields. Additional materials: www.superdatascience.com/454
Stephen Welch joins to go over his year-end 2020 list of 10 important questions and pain points that machine learning can improve. In this episode you will learn: Welch Labs on YouTube [4:54] What Stephen’s been up to [7:56] Stephen’s 2020 year-end blog post [10:11] Stephen’s reflections on 10 areas worth focusing on [16:25] Additional materials: www.superdatascience.com/453
In this week’s episode, I discuss how technology propelled the recruitment industry forward and continues to do so today. Additional materials: www.superdatascience.com/452
Dan Shiebler joins us to discuss his category theory Ph.D. program, his full-time job at Twitter, and how the two crossover and combine in his overall data work. In this episode you will learn: Dan’s neuroscience undergrad and MATLAB [4:12] Dan’s Ph.D. timeline and research [14:01] How to start a Ph.D. while working full time [22:45] Dan’s work at TrueMotion and label data [30:39] Dan’s title and role at Twitter [39:15] Specific projects at Twitter [44:09] What skills someone should bring to a T...
This week, Jon talks with Steve Fazzari about the physical and emotional benefits of practicing Yoga Nidra. Additional materials: www.superdatascience.com/450
Ayodele Odubela joins us to discuss fairness in AI and how we can work towards a more equitable and transparent world of data science and machine learning. In this episode you will learn: Comet ML [3:22] What is a data science evangelist? [7:08] FullyConnected [12:04] Imposter Syndrome and Ayodele’s book [15:57] What Ayodele wished she learned from grad school [20:25] Uncovering Bias in Machine Learning [27:00] Where can we affect this positive change in fairness? [31:08] The potential for a ros...
This week, I answer your questions about how to take yourself from data science practitioner to data science leader. Additional materials: www.superdatascience.com/448
Michael Segala joins us to discuss how machine learning can provide creative and novel solutions to longstanding problems in both the private and public sectors. In this episode you will learn: SFL Scientific [4:20] SFL’s example work [10:55] Public sector vs private sector work [20:28] Michael’s day-to-day [30:18] What is Michael looking for in the people he hires? [33:38] Michael’s career journey [41:39] What is Michael excited about for the future? [48:38] Additional materials: www.superdatas...
This week I answer your questions about machine learning and how to educate yourself further in the field. Additional materials: www.superdatascience.com/446
Sinan Ozdemir joins us to share his work in conversational AI and what it takes to keep chatbots up to date and functional in an ever-changing world. In this episode you will learn: Kylie.ai under Directly [4:51] Sinan’s day-to-day work and tools [10:45] Use cases [18:27] AutoML’s role in these processes [21:55] What hard or soft skills are needed for this work? [29:32] Sinan’s background in teaching [34:58] Sinan’s history in pure math and applied math [39:44] Sinan’s math tattoos [43:48] Addit...
In today’s episode, I answer your questions on how to best future-proof your data science career in AI, AutoML, and model interpretability. Additional materials: www.superdatascience.com/444
Jeff Wald joins us to discuss his book and the research he has done into the data and trends around the job market, the decline of the 9-5 office job, and more. In this episode you will learn: The Birthday Rules [3:51] A history of work [7:41] The myth of the lifetime contract [12:15] What the data says about now [21:02] On-demand labor market [25:34] Remote work [32:09] What role will automation play? [46:27] Future of employment from the study lens [48:30] Additional materials: www.superdatasc...
