Accomplished ML professionals share their experiences | Hear engineers, entrepreneurs, and other seasoned members of the global AI community working in AICollection of 22 Posts
Andrew Ng on How His Updated Machine Learning Specialization Can Help You Break Into AI
In the mid-2000s, AI was still just a curiosity to the world at large. At Stanford University, however, one of the most popular classes on campus was Andrew Ng’s CS229 machine learning course. Enrollment was frequently too large to fit in the classroom, yet he wanted even more people to be able to master machine learning.
So, working with a few students, he created an online Machine Learning course that could be taken by anyone with an internet connection and a desire to learn. The rest is history. Coursera launched in 2012 with Machine Learning as its flagship title. It was also the platform’s most popular, with almost 5 million enrollments.
This year, to celebrate the course’s 10 year anniversary, DeepLearning.AI and Stanford Online released a successor — the Machine Learning Specialization. Andrew spoke with us about how the new Specialization improves on the original, who should take it, and how it fits into the modern AI builder’s career arc.
Working AI: How an Accomplished Data Scientist Found Job Satisfaction
Kulsoom Abdullah pivoted from network security into a data science role after taking Andrew Ng’s original Introduction to Machine Learning course from Stanford in 2013. A self-described learning addict, she has taken more than 10 online courses, most recently the Deep Learning Specialization. Outside of work, she’s a fitness fanatic, and was the first competitive weightlifter to compete professionally for Pakistan — after winning a fight to change the dress code to allow religious head coverings. On top of all that, she’s a travel
Working AI: How a Determined Entrepreneur Used Deep Learning to Grow His Business
Kai Saksela is the CEO of NL Acoustics, a Finnish technology startup that designs and manufactures AI products to analyze sounds. He took the Deep Learning Specialization primarily because he loves learning new skills and has been fascinated by the field for a long time. He also had a hunch that neural networks would help his company solve a core problem: providing customers guidance on what they should do when their equipment starts making strange noises. He spoke with us about how his hunch paid off and why AI plays a central role in his company’s growth.
Working AI: Stoking GPU Clusters With Swetha Mandava
Title: Senior Deep Learning Engineer, Nvidia Location: Santa Clara, California Education: Bachelor of Technology, Electronics and Communication Engineering, Manipal University; MS, Electrical and Computer Engineering, Carnegie Mellon University Favorite areas: Natural language processing, autoML, and interpretable AI Favorite researchers: Christopher…
Working AI: Building Bespoke Models With Jade Abbott
Jade Abbott turned a childhood desire for a robotic best friend into a career training computers to understand human language. Having studied AI in school, she got her first job coding conventional software, but she found ways to apply machine learning to her work until that became central to her role. In the meantime, she founded an open source project to train NLP models on African languages. She spoke with us about her fascination with language, the importance of community, and how to incorporate wine into your learning practice.
Working AI: Scheduling Pilots With Ronisha Carter
Public service runs deep in Ronisha Carter’s family. Her mother was a Navy medical technician, and her father worked for the Air Force in information management. The two parents ignited a sense of curiosity and love of learning that led Ronisha and her siblings to explore technology. Her sister was the first in the family to earn a Bachelor’s degree, and her brothers became software developers. Ronisha joined the Air Force and went on to earn a Bachelor’s in computer science and a Master’s in computer engineering before carving a unique path for herself in AI.
Working AI: Transforming Real Estate With Jasjeet Thind
As a child, Jasjeet Thind led the other kids at his daycare to engage in shenanigans. He still exercises his leadership skills, but instead he uses them to organize Zillow’s army of engineers as they aim to automate everything about real estate. Thind became fascinated with data as a college student at Cornell University in the 1990s, and his career exploded along with the deep learning revolution. Read more.
Working AI: Adama Diallo on Computer Vision and Diversity in AI
Growing up in Mauritania, Adama Diallo was fascinated by the human brain. Now, as an AI developer at the software company Paradigm, he’s using artificial intelligence to map architectural spaces. In this edition of our Working AI series, Adama discusses his projects, advice for learners, and views on social bias in the industry. Read more.
Working AI: At the Office with Research Scientist Archis Joglekar
While much of the AI revolution has served consumers, AI has a lot to offer to other aspects of society. I work at Noble.AI mainly because it gives me the opportunity to stay close to science. At Noble.AI, we’re building software that speeds up the work of scientists, researchers, and engineers by 10 to 100 times.
Working AI: At the Office with MLE Ruben Sipos
Location: San Francisco, California Age: 33 Education: B.Sc. in Computer Science and Mathematics, 2009, University of Ljubljana, PhD in Computer Science, 2014, Cornell University Years in industry: 5 Favorite movie: Event Horizon (1997) Favorite machine learning researcher: Thorsten…
Working AI: At the Office with Data Scientist Joe Gambino
Working at IDEO has let me work on a wide range of problems: I’ve used clustering and dimensionality reduction to create a prototype that communicates health data while encouraging empathy and engagement. I’ve run traffic simulations to assess the size of delivery markets and prototyped animated, interactive explanations inspired by those simulations. I’ve built internal React web-apps for collecting data and texting customers.