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Algorithm
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A

Algorithm
Artificial Intelligence (AI)
AutoML

B

Backpropagation
Bagging
Basic terms
Boosting

C

Classification
Clustering
Computer Vision
Confusion matrix
Content Extraction
Cross-validation

D

Data
Data preparation
Data Science (DS)
Deep Learning (DL)
Deployment
Digital Transformation
Dimensionality reduction

E

Ensemble
Explainable AI (XAI)
Exploratory data analysis (EDA)

F

Face recognition
Feature
Feature engineering
Feature selection

I

Image recognition
Image segmentation
Information

L

Loss function

M

Machine Learning (ML)
Machine Translation
Machine Vision
ML pipeline
Model
Model evaluation
Model monitoring
Model training
Model tuning

N

Natural Language Processing (NLP)
Neural Network (NN)

O

Overfitting and Underfitting

P

Pattern recognition

Q

Question Answering

R

Regression
Reinforcement Learning (RL)

S

Sentiment Analysis
Speech recognition
Speech-to-text
Stacking
Supervised Machine Learning

T

Text Classification
Text generation
Text-to-speech
Train, validation, and test sets

U

Unsupervised Machine Learning

Basic terms

It is essential to understand the basic terminology and frequently used terms in AI and Data Science for realizing how it can be applied.

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+38 099 055 23 92

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