Laurence Moroney, the head of Developer Advocacy for AI at Google, and Karmel Allison, leading a team of engineers working to make TensorFlow high-level APIs easy to use, are giving a great talk on Machine learning.
This is a talk for people who know code, but who don’t necessarily know machine learning. Learn the ‘new’ paradigm of machine learning, and how models are an alternative implementation for some logic scenarios, as opposed to writing if/then rules and other code. This session will guide you through understanding many of the new concepts in machine learning that you might not be familiar with including eager mode, training loops, optimizers, and loss functions.
Speakers: Laurence Moroney and Karmel Allison
Laurence Moroney is the head of Developer Advocacy for AI at Google with a mission to change the world for developers by equipping them for the ML and AI revolution. As the author of more programming books than he can count, he’s excited to be working with deeplearn.ai and Coursera in producing video training. He teaches the popular TensorFlow specialization at Coursera with Andrew Ng, and is a regular keynote speaker at events around the world. As the owner of the TensorFlow and Google AI channels on YouTube, he has also worked extensively to understand what makes developers tick, and how companies like Google can do better at eliminating bias.
Karmel Allison leads a team of engineers working to make TensorFlow high-level APIs easy to use and flawless to scale. She received her PhD in Bioinformatics from the University of California, San Diego, and has over ten years of experience in software development and machine learning. Previously led engineering teams building a DNA sequencer at Genia and serving real-time recommendations at Quora.