Welcome to TensorFlow, from basics to mastery. Some of you may have taken deep learning or machine learning from me and learned about the amazing things you can now do with deep learning machine learning. One of the best tools you can use to implement these algorithms is TensorFlow. Learning algorithms can be quite complicated, and today, programming frameworks like TensorFlow, PyTorch, caffe, and many others can save you a lot of time. These tools can be complicated and what this set of courses will do is teach you how to use TensorFlow effectively. In order to teach much of these courses, I'm absolutely thrilled to introduce Laurence Moroney. >> Thank you, Andrew. >> He is a developer advocate at Google and has been working on Google AI and TensorFlow. Lawrence has also written over 30 programming books including four sci-fi novels. >> Yeah exactly, I've been busy. I really enjoy writing, but the one thing I enjoy even more is learning and teaching AI. Actually, I've learned from the specializations that you mentioned and I learned from your courses. So it's a real honor to be here with you. >> Thank you. I did not know that you were taking my course as well. Thank you. >> Definitely, so as a big fan, and that's really what got me into AI was, it's actually long story, I started doing AI many, many years ago back when it was things like Prolog and Lisp and all that. But now when we've gotten more into machine learning and deep learning with neural networks, I needed a place to learn, and I actually learned it from your courses, so it's been exciting to be actually coming full circle and now teaching it myself, too. >> Thank you. I actually did not know that. Thank you for sharing that. >> I caught you by surprise. >> Yes. >> [LAUGH] >> So, where the industry is at right now is one of the things that really excites me, because it's just, it's really exploding, right? There's deep learning and machine learning skills are becoming ever more important and opening up whole new scenarios. >> One of the strange things and exciting things about machine learning and AI is that it is no longer just a technical thing limited to the software industry so that everyone in all this - every industry needs to figure this out. >> Yeah, and it's exciting from a developer's perspective because there's a new paradigm, and the new paradigm to me is opening up scenarios that weren't previously possible, things that were too difficult for me to write programs for. And it's like whenever a new paradigm comes, and these new tools come, and it can open up new scenarios, then that opens up great new opportunities. >> Yeah, and I think one of the tragic things today is, even though the whole world sees the promise and the hope of these machine learning AI capabilities changing so many things, the world just doesn't have enough AI developers today. >> Exactly. I mean I've seen surveys of 25, 26 million software developers and maybe 300,000 AI practitioners. So part of my personal passion is to try and turn those 24.7 non-AI practitioners, a significant portion of them into people who can understand AI and who can build the new and exciting things that we can't think of. >> So I think if you finish this set of courses and learn how to code in TensorFlow, hopefully that will help you do some of this exciting work and maybe become an AI developer. So, in the next video, you will hear Laurence talk about the differences between traditional programming paradigms versus the machine learning, and deep learning programming paradigms. And you'll also hear about how to fit in x to y data relationship, how to fit a straight line to data. So please go on to the next video. >> Thank you.