Become a machine learning pro!
Google TensorFlow has become the darling of financial firms and research organizations, but the technology can be intimidating and the learning curve is steep. Luckily, TensorFlow For Dummies is here to offer you a friendly, easy-to-follow book on the subject. Inside, you’ll find out how to write applications with TensorFlow, while also grasping the concepts underlying machine learning―all without ever losing your cool!
Machine learning has become ubiquitous in modern society, and its applications include language translation, robotics, handwriting analysis, financial prediction, and image recognition. TensorFlow is Google's preeminent toolset for machine learning, and this hands-on guide makes it easy to understand, even for those without a background in artificial intelligence.
- Install TensorFlow on your computer
- Learn the fundamentals of statistical regression and neural networks
- Visualize the machine learning process with TensorBoard
- Perform image recognition with convolutional neural networks (CNNs)
- Analyze sequential data with recurrent neural networks (RNNs)
- Execute TensorFlow on mobile devices and the Google Cloud Platform (GCP)
If you’re a manager or software developer looking to use TensorFlow for machine learning, this is the book you’ll want to have close by.
- Explore the underlying machine learning concepts
- Deploy TensorFlow applications to the Google Cloud Platform
- Learn TensorFlow modules and create a neural network
Discover the magic of machine learning
TensorFlow, Google's free toolset for machine learning, has a huge following among corporations, academics, and financial institutions. With the guidance of this book, you can jump on board, too! TensorFlow For Dummies tames this sometimes intimidating technology and explains, in simple steps, how to write TensorFlow applications. Along the way, you'll get familiar with the concepts that underlie machine learning and discover some of the ways to use it in language generation, image recognition, and much more.
Inside ...
- Write machine learning apps
- Work with TensorFlow modules
- Apply statistical regression
- Code distributed applications
- Analyze images and text
- Use deep neural networks
- Categorize data sets
- Build TensorFlow estimators