Step by step tutorial on how to recognize cats in a list of images using Machine Learning and AI in Python

I’ll guide you through the process of recognizing cats in a list of images using machine learning and AI in Python. We’ll be using a popular deep learning framework called TensorFlow and its high-level API called Keras. Let’s get started!

Step 1: Set up the environment Before we begin, make sure you have Python installed on your system. You’ll also need to install the following libraries:

• TensorFlow: pip install tensorflow
• Keras: pip install keras
• Matplotlib: pip install matplotlib
• Numpy: pip install numpy

Step 2: Collect cat images To recognize cats, you’ll need a dataset of cat images for training the model. You can either collect the images manually or download a pre-existing dataset. Popular cat image datasets include the Cat vs Dog dataset and the Oxford-IIIT Pet Dataset. For this tutorial, let’s assume you have a folder called ‘cat_images’ containing cat images.

Step 3: Preprocess the data Before training the model, we need to preprocess the images. This involves resizing the images, normalizing pixel values, and splitting the data into training and validation sets.