1. Building an Image Classifier with Sequential API Using Fashion MNIST Dataset

In this tutorial, we will guide you through the process of building a powerful image classifier using TensorFlow's Sequential API and the Fashion MNIST dataset. Fashion MNIST is a popular dataset of 60,000 28x28 grayscale images of 10 different fashion categories, making it an excellent starting point for training image classifiers.

We will cover the following steps:

Loading and preparing the Fashion MNIST dataset
Preprocessing the data for neural network input
Building a simple deep learning model using the Sequential API
Compiling and training the model
Evaluating the model's performance
Making predictions on new data
By the end of this video, you will have a solid understanding of how to build a neural network for image classification and be able to apply these concepts to other image recognition tasks. Whether you're a beginner or intermediate learner in deep learning, this tutorial is perfect for you!

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Tools & Libraries:

TensorFlow
Keras
Fashion MNIST Dataset
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