Deep Learning with Neural Networks and TensorFlow

Dive into the world of deep learning with this comprehensive tutorial on creating a neural network model using TensorFlow and the MNIST dataset. Learn how to build a deep neural network from scratch, working with 60,000 training samples and 10,000 testing samples of hand-written digits. Explore the process of using pixel values as features to predict numbers from 0 to 9. Gain insights into how neural networks create inner models of pixel relationships to accurately classify new examples. Follow along as the instructor guides you through the implementation, covering topics such as introduction, recap, TensorFlow basics, neural network modeling, bias, and output layers.