From the course: Full-Stack Deep Learning with Python

Unlock this course with a free trial

Join today to access over 25,300 courses taught by industry experts.

Preparing data for image classification using CNN

Preparing data for image classification using CNN - Python Tutorial

From the course: Full-Stack Deep Learning with Python

Start my 1-month free trial Buy for my team

Preparing data for image classification using CNN

“

Here I am on a brand new Colab Notebook EMNIST classification using convolutional neural networks. Now a new notebook implies a new Colab runtime, which means we'll need to restart MLflow on this local machine. The P4 at the bottom right refers to the P4 GPU. That's what we'll use to train our image classification convolutional neural network on the EMNIST data. Now we'll need to install the libraries once again because we are on a new runtime. Torch, Matplotlib, NumPy, and Pandas, we need all of these. We also need PyTorch Lightning, because we'll be setting up our model using PyTorch Lightning, and we also need MLflow. This will get us MLflow 3.9.0, the latest version at the time of this recording. If the version has changed, make sure you explicitly install MLflow 3.9.0 so that you can follow along with this demo exactly. Once you've installed all of these libraries, you may be prompted to restart your current Colab session, so that the new libraries are available to you. And we…

Contents