Intro to Deep Learning (ML Tech Talks)

An overview of Deep Learning, including representation learning, families of neural networks and their applications, a first look inside a deep neural network, and many code examples and concepts from TensorFlow. This talk is part of a ML speaker series we recorded at home. You can find all the links from this video below. I hope this was helpful, and I’m looking forward to seeing you when we can get back to doing events in person. Thanks everyone! Chapters: 0:00 - Intro and outline 1:42 - demos discussion 3:58 - AI vs ML vs DL 7:55 - What’s representation learning? 8:40 - A cartoon neural network (more on this later) 9:20 - What features does a network see? 10:47 - The “deep” in “deep learning” 12:48 - Why tree-based models are still important 13:38 - How your workflow changes with DL 14:02 - A couple illustrative code examples 17:59 - What’s a hyperparameter? 19:44 - The skills that are important in ML 20:48 - An example of applied work in healthcare 21:58 - Families of neural networks ap