TensorFlow 2 for Deep Studying Specialization

SKILLS YOU WILL GAIN

• Tensorflow
• keras
• TensorFlow Likelihood
• Probabilistic Neural Networks
• Deep Studying
• Probabilistic Neural Community
• Generative Mannequin
• Probabilistic Programming Language (PRPL)

About this Specialization

This Specialization is meant for machine studying researchers and practitioners who’re looking for to develop sensible abilities within the common deep studying framework TensorFlow.

The primary course of this Specialization will information you thru the elemental ideas required to efficiently construct, practice, consider and make predictions from deep studying fashions, validating your fashions and together with regularisation, implementing callbacks, and saving and loading fashions.

The second course will deepen your data and abilities with TensorFlow, in an effort to develop totally customised deep studying fashions and workflows for any utility. You’ll use decrease degree APIs in TensorFlow to develop advanced mannequin architectures, totally customised layers, and a versatile knowledge workflow. Additionally, you will broaden your data of the TensorFlow APIs to incorporate sequence fashions.

The ultimate course specialises within the more and more essential probabilistic method to deep studying. You’ll discover ways to develop probabilistic fashions with TensorFlow, making explicit use of the TensorFlow Likelihood library, which is designed to make it straightforward to mix probabilistic fashions with deep studying. As such, this course will also be considered as an introduction to the TensorFlow Likelihood library.

Prerequisite data for this Specialization is python 3, common machine studying and deep studying ideas, and a strong basis in likelihood and statistics (particularly for course 3).

Utilized Studying Challenge

Inside the Capstone initiatives and programming assignments of this Specialization, you’ll purchase sensible abilities in creating deep studying fashions for a variety of functions resembling picture classification, language translation, and textual content and picture era.