Predictive Analytics with TensorFlow 7.1: Deep Learning for Better Predictive Analytics

The video tutorial covers predictive analytics, focusing on deep learning and its advantages over classical machine learning methods. It explains the structure and function of artificial neural networks, including perceptrons and deep neural networks. The tutorial also discusses multilayer perceptrons and their training using backpropagation and gradient descent methods.

What is a key advantage of deep learning over classical machine learning methods?

• It requires less data for training.

• It can automatically extract important features from large datasets.

• It is faster to train on small datasets.

• It does not require any computational resources.

In the context of deep learning, what is the primary task when recognizing animals in images?

• Defining the animal's habitat.

• Manually selecting features like whiskers and ears.

• Automatically extracting features for classification.

• Using K-means clustering for image classification.

What is the role of dendrites in biological neurons?

• They produce electrical impulses.

• They receive signals from other neurons.

• They store genetic information.

• They transmit signals to other neurons.

What is a perceptron in the context of neural networks?

• A type of unsupervised learning algorithm.

• A complex neural network with multiple layers.

• A method for optimizing neural network weights.

• A simple neural network architecture inspired by biological neurons.

What differentiates a deep neural network (DNN) from a simpler neural network?

• DNNs have fewer neurons.

• DNNs have multiple hidden layers.

• DNNs are only used for regression tasks.

• DNNs do not use activation functions.

What is the purpose of the activation function in a neural network layer?

• To initialize the network weights.

• To introduce non-linearity into the model.

• To compute the weighted sum of inputs.

• To connect neurons from different layers.

What is the primary function of a multilayer perceptron (MLP)?

• To perform unsupervised learning.

• To solve both classification and regression problems.

• To replace convolutional neural networks.

• To only handle binary classification tasks.

Which method is commonly used to train a multilayer perceptron?

• Forward propagation

• K-means clustering

• Backpropagation

• Random forest

What is the role of the gradient descent method in training neural networks?

• To increase the cost function.

• To optimize network weights by minimizing the cost function.

• To perform feature extraction.

• To initialize the network's weights.

In a multiclass classification task using MLP, what is typically used in the output layer?

• A linear regression model

• A shared softmax function

• A single activation function

• A decision tree