AND ANSWERS SURE A+
✔✔Turing Test - ✔✔A test of whether a machine displays behavior that appears
intelligent in conversation.
✔✔Machine learning - ✔✔Algorithms learn patterns from past data instead of relying
only on explicitly programmed rules.
✔✔Deep learning - ✔✔A subset of machine learning using multilayer neural networks
for complex pattern recognition.
✔✔Technologies benefiting from deep learning - ✔✔Image recognition, speech
recognition, language translation, and autonomous systems.
✔✔Computer vision - ✔✔The broader AI field focused on enabling computers to
interpret visual information.
✔✔Machine vision - ✔✔A more applied or industrial use of visual systems for
inspection, control, and automation.
✔✔NLP - ✔✔Natural Language Processing; enables computers to understand,
generate, and work with human language.
, ✔✔Cognitive computing - ✔✔AI inspired by cognitive science that uses learning,
reasoning, NLP, and pattern recognition.
✔✔Augmented reality - ✔✔Technology that overlays digital information onto the real
environment in real time.
✔✔Knowledge acquisition - ✔✔Capturing expert knowledge and translating it into a
form a computer system can use.
✔✔Robot - ✔✔A machine or device that can sense its environment and act with some
level of autonomy.
✔✔Categories of robots - ✔✔Preset, collaborative, stand-alone, remote-controlled, and
supplementary robots.
✔✔Nature of data - ✔✔Data is a collection of facts gathered from observations,
experiences, or experiments.
✔✔Data to knowledge idea - ✔✔Data is the raw material from which information and
knowledge are derived.
✔✔Analytics-ready data metrics - ✔✔Reliability, accuracy, accessibility,
security/privacy, richness, consistency, timeliness, granularity, validity, and relevancy.
✔✔Structured data - ✔✔Data organized in rows and columns for easy computer
processing.
✔✔Unstructured data - ✔✔Data such as text, images, audio, and video that lacks a
fixed relational format.
✔✔Semi-structured data - ✔✔Data with some organizational markers or tags, such as
XML, HTML, and log files.
✔✔Data preprocessing - ✔✔Preparing dirty or incomplete data for analysis through
cleaning, transformation, integration, and reduction.
✔✔Data consolidation - ✔✔Combining data from multiple sources into a consistent
dataset.
✔✔Data cleaning - ✔✔Correcting missing, inaccurate, duplicate, or inconsistent data.
✔✔Data transformation - ✔✔Changing data into a more useful or compatible format for
analysis.