Introduction to Deep Learning

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What is the purpose of supervised learning?

Classifying data based on known patterns

What is a characteristic of good features for classification in machine learning?

Being consistent across different lighting conditions

What is the main challenge when applying algorithms to data they were not trained on?

Ensuring high performance without prior training

In machine learning, what is the role of AdaBoost in feature extraction?

Crafting input features for classification Signup and view all the answers

What distinguishes unsupervised learning from supervised learning?

Supervised learning focuses on classifying known patterns. Signup and view all the answers

Why are characteristics like being easily tracked and consistent important for features in machine learning?

To maintain feature quality across various scenarios for accurate classification. Signup and view all the answers

What is the main purpose of unsupervised learning algorithms?

To organize and describe the structure of data without using labeled information Signup and view all the answers

How does semi-supervised learning differ from supervised learning?

Semi-supervised learning uses a combination of labeled and unlabeled data, while supervised learning only uses labeled data Signup and view all the answers

What is the key objective of reinforcement learning?

To explore different actions and monitor their results to determine the optimal approach Signup and view all the answers

Which of the following is not a common application of machine learning?

Analyzing the syntactic structure of sentences Signup and view all the answers

What is the main difference between supervised and unsupervised learning?

Supervised learning uses labeled data, while unsupervised learning uses unlabeled data Signup and view all the answers

What is the primary goal of semi-supervised learning?

To learn from a combination of labeled and unlabeled data and use the unlabeled data to label new data Signup and view all the answers

What is the primary objective of machine learning?

To identify patterns in data and make general predictions Signup and view all the answers

Which type of machine learning algorithm is typically used when there is no answer key or human operator to provide instruction?

Unsupervised learning Signup and view all the answers

What is a key difference between supervised and unsupervised learning?

Supervised learning requires a known dataset with inputs and outputs, while unsupervised learning does not Signup and view all the answers

Which field of application has deep learning already proven to be suitable for?

Computer vision, natural language processing, and speech recognition Signup and view all the answers

What is the connection between deep learning and the neural networks in the human brain?

Deep learning is a subset of machine learning, which is inspired by the neural networks in the human brain. Signup and view all the answers

What is the role of GPUs in deep learning applications?

GPUs are chosen for deep learning applications because of their ability to process large amounts of data quickly. Signup and view all the answers

What type of data can be represented as a 2D tensor?

Multi-channel image Signup and view all the answers

In the context of tensors, what does EGA represent?

Generalized matrix Signup and view all the answers

What is the purpose of manipulating data structures to tensor form?

To achieve near peak performance on CPUs and GPUs Signup and view all the answers

What structure in a neuron receives input from other neurons?

Dendrite Signup and view all the answers

What is the function of the cell body in a neuron?

Processing summed inputs Signup and view all the answers

Which term refers to the structure responsible for sending motor instructions to muscles?

Axons Signup and view all the answers

What is the primary purpose of deep learning models?

To express complex representations by approximating a function Signup and view all the answers

Which of the following is NOT a typical machine learning problem that deep learning can address?

Optimization Signup and view all the answers

What is one of the practical advantages of deep learning mentioned in the text?

It allows for the design of large learning architectures as a software development task Signup and view all the answers

What does the text suggest about the representations learned by deep learning algorithms?

They are difficult to understand and express complex functions Signup and view all the answers

What is a key advantage of deep learning compared to traditional machine learning?

It does not plateau when using more data and makes large trained networks a commodity Signup and view all the answers

Based on the text, what is a step involved in applying deep learning?

Building a model and preparing a dataset Signup and view all the answers

Which one is not a scientific field of deep learning?

Robot programming Signup and view all the answers

The general objective of ML is to capture regularity in data to make predictions.

True Signup and view all the answers

AML system is explicitly programmed rather than trained.

False Signup and view all the answers

Write down four types of ML algorithm

<ol> <li>Supervised learning</li> <li>Unsupervised Learning</li> <li>Semi-supervised Learning</li> <li>Reinforcement learning</li> </ol> Signup and view all the answers

In Supervised Learning , the machine is taught by_________

Example Signup and view all the answers

Match

The algorithm makes prediction and is corrected by the operand = Supervised learning There is no answer key or human operator to provide instruction = Unsupervised learning This uses both labelled and unlabelled data = Semi supervised learning This teaches the machine trial and errors. İt learns from past experiences. = Reinforcement learning Signup and view all the answers

Unsupervised learning , the MLA studies data to identify _______

Patterns Signup and view all the answers

_ data is essentially information that has meaningful tags so that the algorithm can understand the data, whilst ___ data lacks that information.

Labeled / unlabelled Signup and view all the answers

________________ focuses on regimented learning process where s MLA is provided with set of actions , parameters and end values

Reinforcement learning Signup and view all the answers

________ are unique properties in the image that are used to classify its objects

Features Signup and view all the answers

Feature extraction —> ________________ —> Classifier Algorithm

Features vector Signup and view all the answers

Write down characteristics of a good feature

Identifiable Easily tracked and composed Consistent across different scales , lighting conditions and viewing angles Still visible in noisy images or when only part of an object is visible Signup and view all the answers

Input images pass through the layers of neural networks so it can learn features layer by layer