How to implement neural networks using TensorFlow?

To build a neural network in TensorFlow, use the Keras API. First, define your network’s structure with either the Sequential or functional API. Add layers such as Dense for standard layers or Conv2D for image tasks. Next, compile your model by choosing an optimizer, a loss function, and the metrics to track. Train your model using the fit() method, setting the number of epochs and batch size. After training, evaluate the model’s accuracy with evaluate() or make predictions with predict(). TensorFlow makes it easy to visualise results and tune model performance with additional tools, helping you optimise each step.