TensorFlow Developer Certificate - Building and Training Neural Network Models using TensorFlow 2.X

This course will teach you how to build, train and evaluate neural network models for classification and regression tasks using TensorFlow 2.X.

Classification and regression are the two most useful machine learning tasks with a lot of real world applications. In this course, TensorFlow Developer Certificate - Building and Training Neural Network Models using TensorFlow 2.X, you’ll learn to build neural network models for classification and regression tasks using TensorFlow 2.X. First, you'll start with the basics of machine learning and neural networks. After that, you'll discover the different evaluation metrics for classification and regression tasks, as well as the problems of overfitting and underfitting, and how to detect and prevent them. Then, you'll understand a classification model to classify images of handwritten digits and a regression model to predict house prices and finally. Finally, you'll learn to build a binary classifier to classify images of dogs and cats using the concept of transfer learning. When you’re finished with this course, you’ll have the skills and knowledge of the practical aspects of implementing the models using TensorFlow. From that perspective, this course will have three demos which will contain full implementations of three models from scratch.

• Course Overview 1min
• Introduction to Neural Networks 35mins
• Build a Neural Network Model for Classification Using Tensorflow 2.9 22mins
• Build a Neural Network Model for Regression Using Tensorflow 2.9 16mins
• Build a Binary Classification Model Using Transfer Learning in Tensorflow 2.9 26mins