IAS Preparation: www.doorsteptutor.com/Exams/IAS/
NET Preparation: www.doorsteptutor.com/Exams/UGC/
CUET PG: www.doorsteptutor.com/Exams/C...
Exam Preparation - www.doorsteptutor.com/Exams/
Masters Level topics: / testprep
NCERTs: / examrace
Hindi Lectures: / examracehindi
Our Websites
www.examrace.com
www.doorsteptutor.com
www.flexiprep.com
www.examtestprep.com
www.jobduniya.com
Call: +91-9998008851
Email: admin@examrace.com
#ugcnet2024 #ugc2024 #ugc2024preparation #upscpreparation #iasprelims2024 #howtoqualifyias #iaspreparationstrategy #doorsteptutor #netpaper1 #ugcnetpreparation #howtoqualifyJRF #iasmains
Algorithm: A set of rules that a machine can follow to learn how to do a task.
Artificial intelligence: This refers to the general concept of machines acting in a way that simulates or mimics human intelligence. AI can have a variety of features, such as human-like communication or decision making.
Autonomous: A machine is described as autonomous if it can perform its task or tasks without needing human intervention.
Backward chaining: A method where the model starts with the desired output and works in reverse to find data that might support it.
Bias: Assumptions made by a model that simplify the process of learning to do its assigned task. Most supervised machine learning models perform better with low bias, as these assumptions can negatively affect results.
Big data: Datasets that are too large or complex to be used by traditional data processing applications.
Bounding box: Commonly used in image or video tagging, this is an imaginary box drawn on visual information. The contents of the box are labeled to help a model recognize it as a distinct type of object.
Chatbot: A chatbot is program that is designed to communicate with people through text or voice commands in a way that mimics human-to-human conversation.
Cognitive computing: This is effectively another way to say artificial intelligence. It’s used by marketing teams at some companies to avoid the science fiction aura that sometimes surrounds AI.
Computational learning theory: A field within artificial intelligence that is primarily concerned with creating and analyzing machine learning algorithms.
Corpus: A large dataset of written or spoken material that can be used to train a machine to perform linguistic tasks.
Data mining: The process of analyzing datasets in order to discover new patterns that might improve the model.
Data science: Drawing from statistics, computer science and information science, this interdisciplinary field aims to use a variety of scientific methods, processes and systems to solve problems involving data.
Dataset: A collection of related data points, usually with a uniform order and tags.
Deep learning: A function of artificial intelligence that imitates the human brain by learning from the way data is structured, rather than from an algorithm that’s programmed to do one specific thing.
Entity annotation: The process of labeling unstructured sentences with information so that a machine can read them. This could involve labeling all people, organizations and locations in a document, for example.
Entity extraction: An umbrella term referring to the process of adding structure to data so that a machine can read it. Entity extraction may be done by humans or by a machine learning model.
Негізгі бет Important AI Terms and Meaning | UGC NET Paper 1 Expected Topics 2024
Пікірлер