Data Science and Machine Learning (Theory and Projects) A to Z - Python for Data Science: TensorFlow for classification

The video tutorial covers the application of neural networks using TensorFlow. It begins with an introduction to TensorFlow and its installation, followed by data preparation using the Titanic dataset. The tutorial then explains how to define a neural network architecture using Keras, train the model, and evaluate its performance. Finally, it explores experimenting with hyperparameters and different optimizers to improve model accuracy.

How many attributes does the Titanic dataset have?

What is the purpose of batch normalization in a neural network?

What does the 'fit' function do in the context of training a neural network?

What is the test accuracy achieved by the model after training?