Skyrocket Your Career by Sharing Your Writing

This week's guest is Khuyen Tran, one of the most preeminent voices of data science: Her blog alone receives over 100k views/month. In this episode, she details how by publishing your writing, you too can skyrocket your career.

Khuyen:
• Became an author for the Towards Data Science blog less than two years ago; already her articles garner 100k+ views per month
• Writes practical daily posts featuring Python code right here on LinkedIn, leading to her developing a highly engaged following of over 25k — in just one year!
• Recently became a technical writer for NVIDIA's Developer Blog
• Has landed four data science jobs, including her current role at Ocelot Consulting, in part thanks to her writing
• Has a perfect 4.0 GPA in the computational and applied mathematics undergraduate degree that she's on track to complete next year

In today's episode, Khuyen fills us in on:
• How publishing your writing can skyrocket your technical career
• Her tricks for maximizing engagement with the content you publish
• Her favorite data science tools and approaches
• Her tricks for prioritizing and being as epically productive as she is across her studies, her data science work, and her prodigious technical writing

And thanks to Krzysztof and Nikolay for the outstanding audience questions that Khuyen addressed on-air.

The episode's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

A.I. for Good

This week's guest is the eloquent and inspiring James Hodson, founder and CEO of the AI for Good Foundation, which leverages data and machine learning to tackle the United Nations' Sustainable Development Goals.

In this episode, James details:
• Globally impactful case studies from his A.I. for Good organization across public health, DEI, and a practical database of A.I. progress on social issues
• How you yourself can get involved in helping apply A.I. for wide-reaching social benefit, whether you're a technical expert or not
• The hard and soft skills that he looks for in the data scientists that he hires

In addition to his leadership of A.I. for Good, James:
• Is an academic research fellow at the Jozef Stefan Institute, where he's focused on Natural Language Processing research
• Is Chief Science Officer at Cognism, a British tech startup
• Served as A.I. Research Manager at Bloomberg LP
• Completed a degree at Princeton University focused on Machine Translation

Thank you to Claudia Perlich for the intro to James! I learned a ton from him while filming this episode.

The episode's available on all major podcasting platforms, on YouTube, and at SuperDataScience.com.

Fail More

Fail more! Failing is very very good. For Five-Minute Friday this week, I elaborate on why.

SuperDataScience episodes are available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Courses in Data Science and Machine Learning

This week's guest is super fun Sadie St. Lawrence, an exceptionally popular data science instructor with over 300k students all-time. She fills us in on her exciting new ML Certificate and the global impact of her Women In Data org.

Sadie:
• Teaches data science at the University of California, Davis
• Her Coursera course is one of the all-time most popular
• Is Founder and CEO of Women in Data, a community of 20k across 15 countries
• Holds a Master's in Analytics from Villanova University

In this episode, she digs into:
• The content of her existing iconic data science course
• The curriculum of her epic forthcoming Machine Learning Certificate
• The mission, impact, and vision of the Women in Data organization
• Her path into data science from music performance
• Non-fungible tokens (NFTs) and the future of technology

Thanks to Harpreet Sahota for introducing me to Sadie! I absolutely loved filming this episode.

Listen or watch here.

Does Caffeine Hurt Productivity? (Part 3: Scientific Literature)

For Five-Minute Friday yesterworkday, I concluded my three-part series on whether caffeine disrupts productivity by broadening from the experiment I ran on myself to the academic literature on the topic.

My Jupyter notebook of data and analysis of the caffeine vs productivity experiment I ran on myself is here.

SuperDataScience episodes are available on all major podcasting platforms and YouTube, and on SuperDataScience.com.

Accelerating Impact through Community — with Chrys Wu

This week's guest is global tech community builder Chrys Wu who details how you too can leverage communities to accelerate your career. This is the first SuperDataScience episode ever recorded in-person!

In addition to accelerating your career with community, Chrys covers:
• K-pop music and its associated cultural movement
• How the Write/Speak/Code and Hacks/Hackers organizations she co-founded leverage community to make a massive global impact for marginalized genders and journalism, respectively
• Her top resources — social media accounts, blogs, and podcasts — for staying abreast of the latest in data science and machine learning

Chrys is a consultant who specializes in product development and change management. She's also a co-founder of both Write/Speak/Code and Hacks/Hackers, the latter of which has grown to 70 chapters across five continents.

Listen or watch here.

Transformers for Natural Language Processing

This week's guest is award-winning author Denis Rothman. He details how Transformer models (like GPT-3) have revolutionized Natural Language Processing (NLP) in recent years. He also explains Explainable AI (XAI).

Denis:
• Is the author of three technical books on artificial intelligence
• His most recent book, "Transformers for NLP", led him to win this year's Data Community Content Creator Award for technical book author
• Spent 25 years as co-founder of French A.I. company Planilog
• Has been patenting A.I. algos such as those for chatbots since 1982

In this episode, Denis fills us in on:
• What Natural Language Processing is
• What Transformer architectures are (e.g., BERT, GPT-3)
• Tools we can use to explain *why* A.I. algorithms provide a particular output

We covered audience questions from Serg, Chiara, and Jean-charles during filming. For those we didn't get to ask, Denis is kindly answering via a LinkedIn post today!

The episode's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Does Caffeine Hurt Productivity? (Part 1)

For Five-Minute Friday this week, I lay out my hypothesis that caffeine decreases people's capacity to focus deeply on work. Next week, we'll review the results of the months-long coffee experiment I ran on myself!

(If you can't wait to see the experiment results, you can head to jonkrohn.com/coffee to check them out.)

Listen or watch here.

Upcoming guest on the SuperDataScience Podcast: Wes McKinney

Next week, I'm interviewing the monumental Wes McKinney — creator of pandas, co-creator of Apache Arrow, and bestselling author of "Python for Data Analysis" — for a SuperDataScience episode.

Got Qs for him? Tweet them @jonkrohnlearns or send them to me on LinkedIn.

Data Science for Private Investing — LIVE with Drew Conway

This week's guest is prominent data scientist and author Dr. Drew Conway. Working at Two Sigma, one of the world's largest hedge funds, Drew leads data science for private markets (e.g., real estate, private equity).

If you aren't familiar with Drew already, he:
• Serves as Senior Vice President for data science at Two Sigma
• Co-authored the classic O'Reilly Media book "ML for Hackers"
• Was co-founder and CEO of Alluvium, which was acquired in 2019
• Advised countless successful data-focused startups (e.g., Yhat, Reonomy)
• Obtained a PhD in politics from New York University

In this episode, he covers:
• What private investing is
• How data science can lead to better private investment decisions
• The differences between creating and executing models for public markets (such as stock exchanges) relative to private markets
• What he looks for in the data scientists he hires and how he interviews them

This is a special SuperDataScience episode because it's the first one recorded live in front of an audience (at the The New York R Conference in September). Eloquent Drew was the willing guinea pig for this experiment, which was a great success: We filmed in a single unbroken take and fielded excellent audience questions.

Listen or watch here.

Deep Reinforcement Learning

Five-Minute Friday today is an intro to (deep) reinforcement learning, which has diverse cutting-edge applications: E.g., machines defeating humans at complex strategic games and robotic hands solving Rubik’s cubes.

You can watch or listen here.

Accelerating Start-up Growth with A.I. Specialists

This week's guest is the game-changing Dr. Parinaz Sobhani. She leads ML at Georgian — a private fund that sends her "special ops" data science teams into its portfolio companies to accelerate their A.I. capabilities.

In this episode, Parinaz details:
• Case studies of Georgian's A.I. approach in action across industries (e.g. insurance, law, real estate)
• Tools and techniques her team leverages, with a particular focus on the transfer learning of transformer-based models of natural language
• What she looks for in the data scientists and ML engineers she hires
• Environmental and sociodemographic considerations of A.I.
• Her academic research (Parinaz holds a PhD in A.I. from the University of Ottawa where she specialized in natural language processing)

Listen or watch here.

...and thanks to Maureen for making this connection to Parinaz!

Building Your Ant Hill

Five-Minute Friday today features my 91-year-old grandmother sharing her insightful life philosophy that centers around an analogy of ants building ant hills.

Listen here.

Bayesian Statistics

Expert Rob Trangucci joins me this week to provide an introduction to Bayesian Statistics, a uniquely powerful data-modeling approach.

If you haven't heard of Bayesian Stats before, today's episode introduces it from the ground up. It also covers why in many common situations, it can be more effective than other data-modeling approaches like Machine Learning and Frequentist Statistics.

Today's episode is a rich resource on:
• The centuries-old history of Bayesian Stats
• Its particular strengths
• Real-world applications, including to Covid epidemiology (Rob's particular focus at the moment)
• The best software libraries for applying Bayesian Statistics yourself
• Pros and cons of pursuing a PhD in the data science field

Rob is a core developer on the open-source STAN project — a leading Bayesian software library. Having previously worked as a statistician in renowned professor Andrew Gelman's lab at Columbia University in the City of New York, Rob's now pursuing a PhD in statistics at the University of Michigan.

Listen or watch here.

Supervised vs Unsupervised Learning

Five-Minute Friday this week is a high-level intro to the two largest categories of Machine Learning approaches: Supervised Learning and Unsupervised Learning.

Listen or watch here.

From Data Science to Cinema

SuperDataScience SuperStar Hadelin returns to report on his journey from multi-million-selling video instructor to mainstream-film actor — and he details the traits that allow data scientists to succeed at anything.

Hadelin has created and presented 30 extremely popular Udemy courses on machine learning topics, selling over two million copies so far. Prior to his epic creative period publishing ML courses, Hadelin studied math, engineering and A.I. at the Université Paris-Saclay and he worked as a data engineer at Google. More recently Hadelin has written a book called "A.I. Crash Course" and was co-founder and CEO of BlueLife AI.

Today's episode focuses on:
• Hadelin's recent shift toward acting in mainstream films
• The characteristics that enable an outstanding data scientist to excel in any pursuit
• How to cultivate your passion and achieve your dreams
• Bollywood vs Hollywood
• How to prepare for the TensorFlow Certificate Program
• Software modules for deploying deep learning models into production

Listen or watch here.

Classification vs Regression

Five-Minute Friday this week is a high-level introduction to Classification and Regression problems — two of the main categories of problems tackled by Machine Learning algorithms.

Listen or watch here.

Deep Reinforcement Learning for Robotics with Pieter Abbeel

Very special guest this week! Pieter Abbeel is a serial A.I. entrepreneur, host of star-studded The Robot Brains Podcast, and the world's most preeminent researcher of Deep Reinforcement Learning applications.

As a professor of Electrical Engineering and Computer Science at the University of California, Berkeley, Pieter directs the Berkeley Robot Learning Lab and co-directs the Berkeley A.I. Research Lab.

As an entrepreneur, he's been exceptionally successful at applying machine learning for commercial value. Gradescope, a machine learning company in the education technology space that he co-founded, was acquired in 2018. And the A.I. robotics firm Covariant, which he co-founded more recently, has raised $147 million so far, including raising $80 million in a Series C funding round in July.

In this episode, Pieter eloquently discusses:
• His exciting current research in the field of Deep Reinforcement Learning
• Top learning resources and skills for becoming an expert in A.I. robotics
• How academic robotics research is vastly different from R&D for industry
• Productivity tips
• Traits he looks for in data scientists he hires
• Skills to succeed as a data scientist in the coming decades

He also had time to answer thoughtful questions from distinguished SuperDataScience listeners Serg Masís and Hsieh-Yu Li.

Listen or watch here.

Managing Imposter Syndrome

The Five-Minute Friday episode this week is on Imposter Syndrome, including what it is and how to manage it.

Thanks to Nikolay for the episode idea and Micayla for doing most of my homework for it!

Listen or watch here.