This course will take you through the steps that a machine learning engineer would take to train and deploy a deep learning model. We will start the course by defining an end goal that we want to achieve. Then, we will download a dataset that will help us achieve that goal. We will build a Convolutional Neural Network using Tensorflow 2 with Keras and then we will train this network on Google AI Platform. After saving the best trained model, we will deploy it as a web app using Flask and Google Cloud Run. Throughout the course, we will be using Docker to containerize our code.
The goal of this course is to make you proficient in training and deploying a deep learning model that was trained using the Tensorflow 2 library.
The course will be a great introduction to Google Cloud Platform if you haven’t used it before. I actually made the course in such a way that even if you never used cloud computing services before, you will still be able to follow along.
I try to deconstruct the difficult concepts and make them easily digestible. My goal is to help you learn these skills and become able to apply them to your real life projects. Whether that be for your actual job or for your side projects.
Specification: Train and Deploy Tensorflow models using Google AI Platform