Category Machine Learning

Data Science at Monsanto with Tim Williamson

http://traffic.libsyn.com/sedaily/Monsanto_Edited_FInal.mp3Podcast: Play in new window | Download “Nothing’s cool unless you call it ‘as a service.’ ” Monsanto is a company that is known for its chemical and biological engineering. It is less well known for its data science and software engineering teams. Tim Williamson is a data scientist at Monsanto, and on today’s show he talked about how he and a small group of engineers at Monsanto dramatically shifted

Continue reading…

Deep Learning and Keras with François Chollet

“I definitely think we can try to abstract away the first principles of intelligence and then try to go from these principles to an intelligent machine that might look nothing like the brain.”

Continue reading…

Machine Learning for Businesses with Joshua Bloom

“You’ve got software engineers who are interested in machine learning, and think what they need to do is just bring in another module and then that will solve their problem. It’s particularly important for those people to understand that this is a different type of beast.”

Continue reading…

TensorFlow with Greg Corrado

“You don’t mind if failures slow things down, but its very important that failures do not stop forward progress.”

Continue reading…

Data Science at Spotify with Boxun Zhang

“I normally try to sit together or very close to a product team or engineering team. And by doing so, I get very close to the source of all kinds of challenging problems.”

Continue reading…

Learning Machines with Richard Golden

“When I was a graduate student, I was sitting in the office of my advisor in electrical engineering and he said, ‘Look out that window – you see a Volkswagon, I see a realization of a random variable.’ ”

Continue reading…

Machine Learning and Technical Debt with D. Sculley

“Changing anything changes everything.”

Technical debt, referring to the compounding cost of changes to software architecture, can be especially challenging in machine learning systems.

Continue reading…

Bridging Data Science and Engineering with Greg Lamp

Current infrastructure makes it difficult for data scientists to share analytical models with the software engineers who need to integrate them. Yhat is an enterprise software company tackling the challenge of how data science gets done. Their products enable companies and users to easily deploy data science environments and translate analytical models into production code.

Continue reading…

Kaggle with Ben Hamner

Data science competitions are an effective way to crowdsource the best solutions for challenging datasets. Kaggle is a platform for data scientists to collaborate and compete on machine learning problems with the opportunity to win money from the competitions’ sponsors.

Continue reading…

Teaching Data Science with Vik Paruchuri

There is a need for more data scientists to make sense of the vast amounts of data we produce and store. Dataquest is an in-browser platform for learning data science that is tackling this problem.

Vik Paruchuri is the founder of Dataquest. He was previously a machine learning engineer at EdX and before that a U.S. diplomat.

Continue reading…