TensorFlow is one of the newest and most comprehensive libraries for implementing deep learning. With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. TensorFlow is an open source software library for numerical computation using data flow graphs. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. Deep learning is the intersection of statistics, artificial intelligence, and data to build accurate models.. If you're interested to hone your skills in building deployable solutions with Google’s TensorFlow library , then go for this Learning Path.
Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.
The highlights of this Learning Path are:
This Learning Path addresses common commercial machine learning problems using Google’s TensorFlow library. It will not only help you discover what TensorFlow is and how to use it, but also show you the unbelievable things that can be done in machine learning with the help of real-world examples and use cases.
You’ll start off with the basic installation of TensorFlow, moving on to covering the unique features of the library such as data flow graphs, training, and visualization of performance with TensorBoard—all within an example-rich context using problems from multiple sources. The focus is on introducing new concepts through problems that are coded and solved over the course of each section. Further, you’ll dive deeper into the hidden layers of abstraction using raw data.
This Learning Path will teach you various complex algorithms for deep learning and various examples that use these deep neural networks. You’ll also learn how to train your machine to craft new features to make sense of deeper layers of data. You’ll come across topics such as logistic regression, convolutional neural networks, recurrent neural networks, training deep networks, high level interfaces, and more. With the help of novel practical examples, you’ll become an ace at advanced multilayer networks, image recognition, and beyond.
Towards the end of this Learning Path, you’ll be able to process data and gain insights that will change the way you look at it, with the efficiency and simplicity of TensorFlow
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