Superdatascience

Greg Coquillo joins us to discuss his work on ROI for startups and the best ways to make the most of your company’s AI investment. In this episode you will learn: Our connection through Harpreet’s happy hours and DSGO [4:48] Greg’s content on LinkedIn [6:40] The scope of Greg’s work [9:25] Making the most out of AI [16:05] LinkedIn Q&A [20:00] Quantum machine learning [32:06] Additional materials: www.superdatascience.com/495

In this episode, I talk about an interesting thought experiment that helps you appreciate your existence. Additional materials: www.superdatascience.com/494

Anjali Shrivastava joins us to discuss her data science degree and her content creation efforts to bring data science to the people. In this episode you will learn: Anjali’s studies [2:00] Anjali’s YouTube channel [11:57] The content creation process [17:58] Yoga during the pandemic [21:34] Anjali as a writer [24:38] Anjali’s dual degrees [31:28] Anjali’s previous data science roles [43:04] Anjali’s first full-time data job [51:12] Anjali’s hopes for the future [55:29] Additional materials: www.superdatascience.com/493

In this episode, I discuss the changing child mortality rate as evidence of how much better the world is and how much better it could be. Additional materials: www.superdatascience.com/492

Veerle van Leemput joins us to make the case for why you should be using R for production. In this episode you will learn: Our shared powerlifting passion [2:47] The stigma of using R [12:02] What does Analytic Health do? [13:55] How Analytic Health uses R [19:08] Tidyverse [34:44] Tools for API creation [37:09] Additional materials: www.superdatascience.com/491

In this episode, I discuss why you should avoid the visually pleasing but flawed pie chart. Additional materials: www.superdatascience.com/490

Vin Vashishta joins us to discuss his AI consulting work and his philosophy on AI strategy for monetization. In this episode you will learn: V-Squared [4:59] Vin’s online content [17:18] Low-code/no-code in data science [25:33] Top five gap skills [35:19] Data sets for insights on consumers and targeting [40:26] Are there socially beneficial data science and machine learning applications? [43:16] The most difficult data science problem Vin ever faced [50:39] Additional materials: www.superdatascience.com/489

In this episode, I discuss the simple and cheap ways you can buy yourself more time during the day. Additional materials: www.superdatascience.com/488

Susan Walsh joins us to discuss the importance of data cleaning and normalization and how clean procurement data can save companies money. In this episode you will learn: Susan’s “COAT” system [7:16] The Classification Guru [15:39] Case studies [22:46] Susan’s book [30:26] Additional materials: www.superdatascience.com/487

In this episode, I go over the world history of calculus and how we still use these techniques today. Additional materials: www.superdatascience.com/486

Doug Eisenstein joins us for a great and in-depth conversation on data engineering in the financial sector. In this episode you will learn: • The founding of Advanti [4:37] • Aristos and solution products [16:45] • The kinds of financial industries and how Doug helps [26:25] • Entity Extraction [34:27] • Temporality data [44:27] • How to work with Doug [58:19] Additional materials: www.superdatascience.com/485

In this episode, I discuss interesting research on why humans are so quick to lose faith in algorithms. Additional materials: www.superdatascience.com/484

Andrew Jones joins us to discuss data science interviews and how you can maximize your chances on interview time, resume, and more! In this episode you will learn: Data Science Infinity [5:40] “The Essential AI and Data Science Handbook for Recruitment” [17:40] How can aspiring data scientists set themselves apart? [21:30] What skillset should data scientists have? [34:36] Should data science be trying to be data engineers? [41:14] How can organizations ensure data science projects are a success? [50:50] Additional materials: www.superdatascience.com/483

In this episode, I talk about the advantages of using a continuous calendar. Additional materials: www.superdatascience.com/482

Kris Tait joins us to discuss the vast world of digital performance marketing and how automation, data, and optimization play an important role. In this episode you will learn: What is performance marketing? [3:29] How can advertisers take advantage of these tactics? [13:04] The importance of quality data in performance marketing [20:19] Human value performance marketing [25:30] How does Croud optimize? [29:05] What are the best KPIs in this industry? [34:02] Roles available at Croud now [39:11] Typical tools at Croud [42:43] What clients work best for Croud? [48:56] Additional materials: www.superdatascience.com/481

In this episode, I go over my top 5 tips for refining your perfect data science resume. Additional materials: www.superdatascience.com/480

Maureen Teyssier joins us to discuss the cutting-edge work Reonomy is doing in commercial property real estate and her views and tips on building a great data science team. In this episode you will learn: Maureen’s work with Reonomy [5:40] Knowledge graphs and use cases [7:35] Other tools Reonomy uses [18:58] What Maureen looks for in potential hires, soft skills and hard skills [26:28] Hiring at Reonomy [41:40] Maureen’s tips for growing a data science team [48:55] Tools to transition from academia to industry [52:45] Additional materials: www.superdatascience.com/479

In this episode, I go over my 5 keys to success to tackle any goal. Additional materials: www.superdatascience.com/478

Sidney Arcidiacono joins us to discuss her studies and work at Make School and her interest in utilizing AI for healthcare, as well as her tips and strategies for becoming a successful early-career data scientist. In this episode you will learn: What is Make School? [5:00] Sidney’s interest in AI and computer science [10:56] Graph theory and graph convolutional neural networks [19:53] What tools does Sidney use for her work? [31:16] Sidney’s internship [36:52] How other beginners can get involved in data science [38:12] Sidney’s goals [41:57] Additional materials: www.superdatascience.com/477

In this episode, I discuss the amazing benefits of implementing peer-driven learning in your professional life. Additional materials: www.superdatascience.com/476