Filtering by Category: Data Science

Fairness in A.I.

Added on March 4, 2021 by Jon Krohn.

Machines increasingly decide on critical aspects of your life, including medical treatment, mortgages, and job applications. Disturbingly, many such algorithms reinforce historical biases against particular gender and ethnic groups.

This week, Ayodele Odubela joins me on SuperDataScience to discuss the importance of equitability, introspection, and transparency when modeling data (and even in hardware development!), plus a bit about Ayodele’s own personal journey as a data scientist.

Ayodele works at Comet (a machine learning company), is the founder of FullyConnected (a brilliantly-named platform for black and brown data scientists), and the author of Getting Started in Data Science as well as the forthcoming book Uncovering Bias in Machine Learning. I learned a lot from Ayodele; she knows a ton and conveys her knowledge beautifully.

Listening/viewing options, as well as full transcript, available here.

How to Be a Data Science Leader

Added on February 26, 2021 by Jon Krohn.

The more leadership responsibility you take on as a data scientist or engineer, the more you accept that can't stay on top of the cutting-edge innovations as much as you might like. Nor do you get to spend as much time as you'd like writing code.

...and that's for the best. It's what what your team and your company need from you.

Commercial ML Opportunities Lie Everywhere

Added on February 25, 2021 by Jon Krohn.

In this week’s SuperDataScience guest episode, the staggeringly experienced Dr. Michael Segala fills us in on how commercial opportunities for applying machine learning to real-world problems are everywhere.

Michael is co-founder and CEO of SFL Scientific, a world-leading A.I.-consulting firm that brings state-of-the-art deep-learning possibilities into production across the public and private sectors alike. We survey opportunities for transformative ML applications in the coming decades across a broad range of industries before focusing on the medical industry and governments in particular.

As NVIDIA’s Partner of the Year for AI services, as well as a consultant to firms as diverse as the US Navy, the Smithsonian Institution, and Johnson & Johnson, Dr. Segala may be better-positioned than anyone to be optimistic about the huge positive social impact data and models will have in our lifetimes.

Listening/viewing options, as well as full transcript, available here.

Getting Started in Machine Learning

Added on February 19, 2021 by Jon Krohn.

On last Friday’s episode, I answered questions from podcast listeners on the “futureproof-ness” of a data science career. This week, I’m answering a few more listener-submitted questions about getting start in ML, particularly if you’re completely new to the field!

From MOOCs, to free videos, to graduate level textbooks, I cover a wide or materials that you can use to become an expert in machine learning.

Conversational A.I. with Sinan Ozdemir

Added on February 18, 2021 by Jon Krohn.

Sinan Ozdemir may be the most articulate explainer of complex concepts I’ve ever met. In the latest SuperDataScience episode, he fills me in on how to design a Conversational A.I. (aka "chatbot") so it's effective for users and businesses alike.

In addition, we discussed AutoML, how a background in pure mathematics is a huge asset in applied data science, and the hard and soft skills you need for a career in natural language processing at a cutting-edge tech company.

Sinan co-founded Kylie.ai, a conversational-AI company, which was acquired by Directly, where Sinan now serves as Director of Data Science. He has a deep well of both technical knowledge and business savvy that I found wildly informative.

Listening/viewing options, as well as full transcript, available here.

Future-Proofing Your Career

Added on February 12, 2021 by Jon Krohn.

At the beginning of 2021, I asked the following on Twitter: “What questions do you have about machine learning as a science or as a career?”

In response, I was asked some terrific questions about data science, many of which are popular ones that I’ve been asked time and again. In today’s FiveMinuteFriday, I’ll answer the ones I thought would be most valuable for everyone to hear the answer to.

Gabriel, who appears to be Brazillian, but indicates his location is “Lost + Found” asked me:

“Is a career in data science really future-proof? What are the odds of another AI winter and a crisis in this career?”

The End of Jobs

Added on February 12, 2021 by Jon Krohn.

We’ve all heard the claim: “Robots will take our jobs.” But what actually happens when work is fundamentally changed by technology? Jeff Wald, author of The End of Jobs and co-founder of WorkMarket, joins me on this episode to discuss the future of our 9-to-5’s including how data science, automation, and other macroeconomic factors will reshape work around the globe in the coming decades.

Jeff’s work involves a careful examination of the data around the history of work, and builds on his own experience as co-founder of WorkMarket, a company focused on helping companies manage contractors. We discuss the pandemic, remote work, and the obligations of society towards the people caught up in the churn.

Listening/viewing options, as well as full transcript, available here.

Communicating Data Effectively

Added on February 7, 2021 by Jon Krohn.

Things can get silly when Kate and I get together 🙃 BUT we also covered a lot in this week’s guest episode of the SuperDataScience, including:

The utter importance of communicating data effectively
Concrete tips for doing so
And how to build a giant social-media presence (like Kate's 150k following!)

Kate is the founder of Story by Data & DATAcated Academy, and author of four books including The Disruptors: Data Science Leaders and Journey to Data Scientist.

Listening/viewing options, as well as full transcript, available here.

MuZero: Learning Without Rules

Added on February 1, 2021 by Jon Krohn.

This article was adapted from a podcast. Listening/viewing options, as well as a full transcript, available here.

On last week's Five-Minute-Friday episode, I introduced the concept of artificial general intelligence ( or AGI, for short), a theoretical algorithm that one day could have all of the intellectual capacities of a human being. I also introduced the company DeepMind and the landmark deep reinforcement learning algorithms they developed over the past decade, each one a stepping stone on the road to creating AGI. If any of AGI, DeepMind, or deep reinforcement learning are unfamiliar terms to you, you might want to check out last week's Five Minute Friday episode to brush up.

Last week's coverage of DeepMind's deep reinforcement learning advances bring me now to MuZero, an algorithm that David Silver and his DeepMind research team published on in the final days of 2020 in the journal Nature, arguably the most prestigious academic science journal.

Deep Learning for Machine Vision

Added on January 28, 2021 by Jon Krohn.

In the latest SuperDataScience episode, the brilliant A.I. researcher Deblina Bhattacharjee fills me in on the state of the art in machine vision. From predicting earthquakes to 3D VR experiences based on ordinary 2D art, she's seemingly in on it all!

We also covered:

Automatic detection of biological cells in medical images
The typical workday of, and software tools used by, A.I. researchers working at the cutting edge
The critical math subjects necessary to be an outstanding machine learning practitioner (to my delight, she reeled off the subjects covered in my ML Foundations curriculum)
The ever-increasing utility of unsupervised learning approaches
Her top productivity tips (Deblina is unbelievably productive so I greatly value her two cents on this!)
Prog rock music
The intelligence of plants (yep, plants!)

This is an outstanding episode. I learned a ton while filming and had a lot of laughs too, so I think you'll enjoy it too.

Listening/viewing options, as well as full transcript, available here.

DeepMind's quest for Artificial General Intelligence

Added on January 22, 2021 by Jon Krohn.

This article is based off of a podcast episode. You can listen to or watch the full episode here.

DeepMind, a London-based subsidiary of Google’s parent company Alphabet, has done it again and pushed the boundaries of what can be achieved in the field of machine learning, thereby pushing the human race one step closer toward developing artificial general intelligence.