Dive into a comprehensive TensorFlow 2.0 tutorial designed for deep learning enthusiasts and professionals. Explore the fundamentals of this popular Python library, from installation to advanced concepts like convolutional neural networks. Learn about tensors, neural network mathematics, and gain hands-on experience with practical applications such as digit classification using the MNIST dataset and building a binary image classifier. Master TensorFlow's capabilities through step-by-step guidance, covering essential topics like tensor manipulation, neural network architecture, and CNN implementation. By the end of this course, develop a solid foundation in TensorFlow 2.0 and enhance your skills in deep learning and artificial intelligence.
Overview
Syllabus
Introduction.
Agenda.
Introduction to TensorFlow.
What are Tensors?.
How to install TensorFlow?.
Introduction to Neural Networks.
Mathematics behind Neural Networks.
Getting started with TensorFlow.
Hands-on sessions using TensorFlow.
Digit classification using MNIST dataset.
How does a Convolutional Neural Network work?.
Binary image classifier with CNNs.
Summary.
Taught by
Great Learning
