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TensorFlow Developer Professional Certificate
Intermediate
Topics
AI Frameworks
Computer Vision
Deep Learning
NLP
Time Series
Congratulations on coming to the end of this first course, and wow, you've come a long way. Yeah, I mean, we've, like, looked at, with the students, like, we've looked at how to use TensorFlow all the way from the beginning, with doing something like fitting a straight line, to then, like, recognizing fashion items. And it was really cool, it was like three lines of code to do a really complicated task like that. And isn't it amazing? Computer vision in three lines like that. And then we improved that by adding convolutions. And we called it an improvement, but that means now four lines of code to define two conv layers and two max pool layers, and then a tool like TensorFlow takes care of a lot of the rest. And then we looked at going beyond, like, the simple images to, like, bigger and colored images, and we didn't even add any lines of code for that, right? It was just changing the shape of the data coming in. So by learning a programming framework like this, you can write very complicated programs with just a few lines of code, and this helps people save a lot of time. But there's still a lot more to learn. Oh, there is. And, like, some of the things that we'd love to explore are things such as, like, when you have very small datasets, that can lead to an error called overfitting. So we'll explore some techniques and tools that we can use to avoid that. And transfer learning, if you can download someone else's, say, TensorFlow model and use that for your own problem, even though it was trained on a totally different dataset, TensorFlow has tools to let you do that efficiently as well. Absolutely. And one of the things that a lot of AI practitioners love to be involved in is, like, there's online competitions where places like Kaggle provide, like, a dataset, and they ask you to build a classifier around that dataset. And we're going to explore some of the skills that you can use to take part in those competitions. So congratulations again on coming to the end of the first course, and there's still all these amazing things to learn about TensorFlow. So please go on to the next course.
