L2: Deep Learning and Machine Learning

Question 1

Term

Answer 1

Definition

Question 2

Artificial Neural Networks

Answer 2

Collections of small computing units (neurons) that process data and learn to make decisions over time.

Question 3

Bayesian Analysis

Answer 3

A statistical technique that uses Bayes’ theorem to update probabilities based on new evidence.

Question 4

Business Insights

Answer 4

Accurate insights and reports generated by generative AI can be updated as data evolves, enhancing decision-making and uncovering hidden patterns.

Question 5

Cluster Analysis

Answer 5

The process of grouping similar data points together based on certain features or attributes.

Question 6

Coding Automation

Answer 6

Using generative AI to automatically generate and test software code for constructing analytical models, freeing data scientists to focus on higher-level tasks.

Question 7

Data Mining

Answer 7

The process of automatically searching and analyzing data to discover patterns and insights that were previously unknown.

Question 8

Decision Trees

Answer 8

A type of machine learning algorithm used for decision-making by creating a tree-like structure of decisions.

Question 9

Deep Learning Models

Answer 9

Includes Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) that create new data instances by learning patterns from large datasets.

Question 10

Five V’s of Big Data

Answer 10

Characteristics used to describe big data: Velocity, volume, variety, veracity, and value.

Question 11

Generative AI

Answer 11

A subset of AI that focuses on creating new data, such as images, music, text, or code, rather than just analyzing existing data.

Question 12

Market Basket Analysis

Answer 12

Analyzing which goods tend to be bought together is often used for marketing insights.

Question 13

Naive Bayes

Answer 13

A simple probabilistic classification algorithm based on Bayes’ theorem.

Question 14

Natural Language Processing (NLP)

Answer 14

A field of AI that enables machines to understand, generate, and interact with human language, revolutionizing content creation and chatbots.

Question 15

Precision vs. Recall

Answer 15

Metrics are used to evaluate the performance of classification models.

Question 16

Predictive Analytics

Answer 16

Using machine learning techniques to predict future outcomes or events.

Question 17

Synthetic Data

Answer 17

Artificially generated data with properties similar to real data, used by data scientists to augment their datasets and improve model training.