Building a basic deep learning model with TensorFlow

TensorFlow, or TF for short, is an end-to-end platform for building ML models. The main focus of the TensorFlow framework is to simplify the development, training, evaluation, and deployment of deep neural networks. When it comes to working with unstructured data (such as images, videos, audio, etc.), neural network-based solutions have achieved significantly better results than traditional ML approaches that mostly rely on handcrafted features. Deep neural networks are good at understanding complex patterns from high-dimensional data points (for example, an image with millions of pixels). In this section, we will develop a basic neural network-based model using TensorFlow. In the next few sections, we will see how Vertex AI can help with setting up scalable and systemic training/tuning of such custom models.

Important Note

It is important to note that TensorFlow is not the only ML framework that Vertex AI supports. Vertex...