🔧You can build a deep image classifier using your own data.
💻The tutorial covers the end-to-end pipeline, including data loading, preprocessing, model building, evaluation, and saving.
🌐You can download images from the web to use as your dataset.
🖼️You can visualize the images using matplotlib.
🚀You can use TensorFlow and Keras to build a deep neural network for image classification.
Can I use my own data to build the image classifier?
—Yes, you can download images from the web and use them as your dataset.
What does the end-to-end pipeline involve?
—The pipeline includes data loading, preprocessing, model building, evaluation, and saving.
How can I visualize the images?
—You can use matplotlib to visualize the images in your dataset.
What tools can I use to build the deep neural network?
—You can use TensorFlow and Keras to build and train the deep neural network.
Can I save the trained model for future use?
—Yes, you can save the trained model to use it later.
00:00Introduction to the tutorial on building a custom deep image classifier using your own data.
01:23Discussion on the project idea and requirements for the image classifier.
03:33Installation of dependencies and setup of TensorFlow and Keras.
04:59Downloading and preparing the dataset of images for training the image classifier.
08:33Preprocessing and loading the dataset into the pipeline for model training.
11:59Building a deep neural network using Keras for image classification.
14:45Evaluating the trained model and testing its performance on the dataset.
17:10Saving the trained model for future use and deployment.
