Cats and Dogs Classification with Pre-trained Neural Network
Learn about the VGG16 pre-trained model architecture and how to create a VGG16 base model using Keras. Learn how to leverage feature representations from the pre-trained model to train and optimize your deep-learning model, and fine-tune your model to improve its performance.
JetBrains Academy
About
Deep neural networks require a large amount of data and computing power to train them from scratch. Collecting and annotating the data is time-consuming and expensive. Even with the right computer, it may take days and weeks to train a deep-learning model with millions of data points. Big IT companies have trained and optimized deep neural networks on these large datasets, and have made these models available to everyone. You can use these pre-trained models as is or customize them to a specific task with transfer learning. In this project, you will learn how to use pre-trained models and transfer learning to circumvent the data and compute resource challenges in training deep-learning models from scratch.
Graduate project
This project covers the core topics of the Data Scientist course, making it sufficiently challenging to be a proud addition to your portfolio.
At least one graduate project is required to complete the course.