Getting Started with TensorFlow 2.0 for Deep Learning

About this course

Deep learning is a trending technology if you want to break into cutting-edge AI and solve real-world, data-driven problems. Google’s TensorFlow is a popular library for implementing deep learning algorithms because of its rapid developments and commercial deployments.

This course provides you with the core of deep learning using TensorFlow 2.0. You’ll learn to train your deep learning networks from scratch, pre-process and split your datasets, train deep learning models for real-world applications, and validate the accuracy of your models.

By the end of the course, you’ll have a profound knowledge of how you can leverage TensorFlow 2.0 to build real-world applications without much effort.

About the AuthorMuhammad Hamza Javed is a self-taught machine learning engineer, an entrepreneur, and an author with over five years of industrial experience. Along with his team, he has been working on several computer vision, machine learning, and deep learning international projects. He learned skills on his own without a direct mentor, so he knows how troublesome it is for everyone to find to-the-point content that improves one’s skillset. He’s designed this course considering the challenges he faced when he learned and in projects, so you don’t have to spend too much time finding what’s best for you.

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