Machine learning algorithms and research are mushrooming due to their accuracy at solving problems. This course walks you through developing real-world projects using TensorFlow in your ML projects.

TensorFlow Machine Learning Projects teaches you how to exploit the benefits—simplicity, efficiency, and flexibility—of using TensorFlow in various real-world projects. With the help of this book, you ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

MLIR, short for Multi-Level Intermediate Representation, will allow projects using TensorFlow and other machine learning libraries to be compiled to more efficient code that takes maximum ...

If you are interested in learning more about how you can use your Raspberry Pi and machine learning to expand your projects, you may be interested in a new tutorial published to the Hackster.io ...

AXA is using a TensorFlow deep machine learning model with 70 variables to predict which customers are likely to have accidents that will cost the insurer more than $10,000, so it can optimize ...

Ubuntu, a Debian-based Linux operating system, offers a perfect platform for machine learning tasks. Known for its ease of use, robustness, and extensive community support, Ubuntu pairs seamlessly ...

Updated with new code, new projects, and new chapters, <i>Machine Learning with TensorFlow, Second Edition</i> gives readers a solid foundation in machine-learning concepts and the TensorFlow library.

TensorFlow has become the most popular tool and framework for machine learning in a short span of time. It enjoys tremendous popularity among ML engineers and developers. According to the Hacker ...

TensorFlow.js – It is a machine learning library to develop models in JavaScript and can use machine learning in the browser or in Node.js directly. A developer can build and train models using ...