IDSC quiz 6

  1. Artificial Intelligence: the ability of a computer to do tasks that are usually done by humans because they require human intelligence.

  2. Biases: an anomaly in the output of machine learning algorithms, due to the prejudiced assumptions made during the algorithm development process or prejudices in the training data.

  3. Deep Learning:  a type of machine learning, runs inputs through a biologically-inspired neural network architecture. 

  4. General AI: is the intelligence of machines that allows them to comprehend, learn, and perform intellectual tasks much like humans. With General AI, machines can emulate the human mind and behavior to solve any kind of complex problem.

  5. Generative Artificial Intelligence (AI) describes algorithms (such as ChatGPT) that can be used to create new content, including audio, code, images, text, simulations, and videos. Fall under the broad category of machine learning.

  6. Machine Learning: algorithms that detect patterns and learn how to make predictions, recommendations and decisions.

  7. Narrow AI: is a specific type of artificial intelligence in which a learning algorithm is designed to perform a single task, and any knowledge gained from performing that task will not automatically be applied to other tasks.

  8. Natural Language: Natural language processing (NLP) refers to the branch of computer science—and more specifically, the branch of artificial intelligence concerned with giving computers the ability to understand text and spoken words in much the same way human beings can.

  9. Neural Networks: This is how the human brain functions: each neuron performs its own simple calculation, and the network formed by all of the neurons multiplies the potential of these calculations.

  10. Supervised Learning:  the machine relies on human intervention. The person provides the bases of the machine’s knowledge so it can then understand how to use them and propose improvements, which will be systematically validated by a human before being implemented.

  11. Unsupervised Learning: the machine doesn’t require this human validation component. It performs the research, identifies new knowledge and memorizes it all on its own.

  12. Business Analytics (BA):  is the process of transforming data into insights to improve business decisions.

  13. Business Intelligence (BI): is the process of analyzing historical and current data, to uncover actionable insights for making decisions.

  14. Data Warehouse: is a type of data management system that is designed to enable and support business intelligence (BI) activities, especially analytics. A data warehouse centralizes and consolidates large amounts of data from multiple sources

  15. Dashboard: is an information management tool used to track, analyze, and display key performance indicators, metrics, and data points. Use a dashboard to monitor the overall health of your business, department, or a specific process.

  16. Democratization of information:  is the process of making digital information accessible to the average non-technical user of information systems, without having to require the involvement of IT. 

  17. Descriptive: this type of data tells what happened, hindsight

  18. Predictive: This type of data describes what will happen, insight.

  19. Prescriptive: This type of data describes how to make it happen, foresight.