Train And Deploy Deep Learning Models
Build your neural network using Keras, train it using Google AI-Platform then deploy it using Flask and Google Cloud Run
What you’ll learn
- Build a deep convolutional neural network using Keras and tensorflow.
- Leverage the power of transfer learning to get high accuracy on your classification task.
- Use google cloud platform to make training and deploying your deep learning model easy and scalable.
- Leverage the power of AI-Platform on Google Cloud Platform to focus on the training of your deep learning model and not on infrastructure.
- Containerize your training code and deployment code to make sure your code runs smoothly and everywhere.
- How to deploy your deep learning model as a web app using Flask and Cloud Run.
- Basic knowledge of Python.
- Basic knowledge of Keras (although I will be explaining the code thoroughly).
- Some knowledge of cloud computing is a plus but not required.
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 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.
Author(s): Nour Islam Mokhtari