Differentiate between Artificial Intelligence (AI) and Machine Learning (ML).

AI and ML are distinct fields.

• AI enables cognitive tasks.

• ML is a subset of AI.

• ML learns from data autonomously.

Fill in the blank: Deep Learning (DL) is characterized by the use of ___ networks to analyze and learn from large amounts of data.

Neural

What is the primary difference between supervised learning and unsupervised learning?

Supervised learning uses labeled data.

• Predictive modeling with labels.

• Unsupervised learns without labels.

• Key for classification tasks.

True or False: Reinforcement learning requires labeled data for training.

False; reinforcement learning relies on a trial-and-error approach to maximize a reward without the need for labeled data.

Riddle: I can learn from my mistakes and improve my performance, but I don’t need to be programmed for every task. What am I?

A machine learning model

Explain the purpose of a training dataset in the context of machine learning.

A training dataset is used to teach the model by providing examples from which it can learn to recognize patterns and make predictions.

Fill in the blank: The layer in a Convolutional Neural Network that reduces the dimensionality of the data while retaining important features is called the ___ layer.

Pooling

What role do labels play in a dataset used for supervised learning?

Labels guide model learning.

• Define target outcomes clearly.

• Enable model training effectively.

• Facilitate performance evaluation easily.

True or False: In a rule-based AI model, the machine has the capability to learn and adapt after its initial training.

False; rule-based models do not learn or adapt after training; they follow predefined rules.

Describe the significance of backpropagation in training neural networks.

Backpropagation improves neural network training.

• Adjusts weights based on errors.

• Enhances model accuracy over time.

• Key in deep learning advancements.

Differentiate between Artificial Intelligence and Machine Learning.

AI simulates human intelligence.

• AI encompasses various technologies.

• ML builds models from data.

• AI solves complex problems.

Fill in the blank: Deep Learning utilizes __________ to analyze large datasets and identify patterns.

Neural networks

What is the role of labels in data used for supervised learning?

Labels guide supervised learning.

• Identify correct outputs.

• Help model learn relationships.

• Essential for training accuracy.

True or False: Unsupervised Learning requires labeled data for training.

False. Unsupervised Learning works with unlabeled data, allowing the model to discover patterns without predefined labels.

In the context of Machine Learning, what is anomaly detection?

Anomaly detection identifies unexpected patterns.

• Finds outliers in data.

• Helps in fraud detection.

• Signals potential issues early.

What are the three main types of learning in the Learning Based Approach?

The three main types are Supervised Learning, Unsupervised Learning, and Reinforcement Learning.

Riddle: I learn from my mistakes but don't need to be told what to do. What am I?

A machine learning model.

Fill in the blank: The Fully Connected Layer in a Convolutional Neural Network is responsible for __________.

Classifying the extracted features from the previous layers into labels.

Explain the concept of backpropagation in Artificial Neural Networks.

Backpropagation optimizes neural networks.

• Adjusts weights to minimize errors.

• Learns from differences in outputs.

• Essential for training deep networks.

Which type of machine learning model is used for predicting continuous outputs?

Regression models are used to predict continuous outputs, such as estimating prices or temperatures based on input data.