Neural Networks and Deep Learning Concepts

What is the primary focus of the workshop introduced in the video?

• Robotics and Automation

• Deep Learning and Image Classification

• Natural Language Processing

• Quantum Computing

Which type of learning involves mapping data points to labels?

• Semi-supervised Learning

• Supervised Learning

• Reinforcement Learning

• Unsupervised Learning

What is the role of activation functions in neural networks?

• To normalize data

• To reduce overfitting

• To introduce non-linearity

• To initialize weights

Which of the following is a common loss function used in training neural networks?

• ReLU

• Sigmoid Function

• Mean Absolute Error

• Softmax

What technique is used to prevent overfitting in neural networks?

• Using more hidden layers

• Reducing the number of epochs

• Dropout

• Increasing the learning rate

In the context of neural networks, what does the term 'backpropagation' refer to?

• The approach of normalizing input data

• The technique of splitting data into training and testing sets

• The method of updating weights based on the error gradient

• The process of initializing weights

Which type of neural network is particularly powerful for image classification tasks?

• Autoencoders

• Generative Adversarial Networks (GANs)

• Convolutional Neural Networks (CNNs)

• Recurrent Neural Networks (RNNs)

What is the purpose of feature extraction in image classification?

• To increase the resolution of images

• To reduce the size of the dataset

• To convert images into numerical data

• To identify and isolate important features from images

Which operation is commonly used in CNNs to reduce the spatial dimensions of the input image?

• Convolution

• Pooling

• Normalization

• Activation

What is the main advantage of using pre-trained models in deep learning?

• They eliminate the need for labeled data

• They require less computational power

• They are always more accurate

• They can be fine-tuned for specific tasks