AI

Artificial Intelligence

Machines that can think/act like humans.

ChatGPT, robots

ML

Machine Learning

AI that learns from data.

Predicting student marks

SL

Supervised Learning

Learns from labeled data.

Spam / not spam email

UL

Unsupervised Learning

Finds patterns without labels.

Customer grouping

RL

Reinforcement Learning

Learns by reward and punishment.

Game AI, robot learning

GAN

Generative Adversarial Network

Creates new realistic data using two networks.

AI-generated faces

CNN

Convolutional Neural Network

Used mainly for images.

Face recognition

RNN

Recurrent Neural Network

Used for sequence data.

Text prediction

LSTM

Long Short-Term Memory

Advanced RNN that remembers long patterns.

Language translation

KNN

K-Nearest Neighbors

Classifies based on nearest examples.

Fruit classification

SVM

Support Vector Machine

Finds best boundary between classes.

Spam detection

DT

Decision Tree

Uses tree-like rules for decisions.

Loan approval

RF

Random Forest

Uses many decision trees.

Disease prediction

NB

Naive Bayes

Probability-based classifier.

Email filtering

LR

Linear Regression

Predicts numeric values.

House price prediction

LogR

Logistic Regression

Predicts yes/no class.

Disease yes/no

K-Means

K-Means Clustering

Groups similar data.

Student performance groups

PCA

Principal Component Analysis

Reduces data size/features.

Image feature compression

NLP

Natural Language Processing

AI for human language.

Translation, chatbot

CV

Computer Vision

AI for images and videos.

Object detection

NN

Neural Network

Model inspired by human brain.

Handwriting recognition

DL

Deep Learning

Neural network with many layers.

Self-driving car

LLM

Large Language Model

AI model trained on large text data.

ChatGPT

AGI

Artificial General Intelligence

Human-level general intelligence.

Future advanced AI

GA

Genetic Algorithm

Solves problems using evolution idea.

Best route finding

AI

Artificial Intelligence

Machines that perform human-like tasks.

ChatGPT, robots

ML

Machine Learning

AI that learns from data.

Marks prediction

DL

Deep Learning

ML using many neural network layers.

Self-driving cars

AGI

Artificial General Intelligence

Human-level general AI.

Future AI concept

XAI

Explainable AI

Explains AI decisions.

Why loan was rejected

SL

Supervised Learning

Learns from labeled data.

Spam / not spam

UL

Unsupervised Learning

Finds patterns without labels.

Customer grouping

RL

Reinforcement Learning

Learns by rewards and punishments.

Game AI

SSL

Semi-Supervised Learning

Uses small labeled + large unlabeled data.

Image classification

Self-SL

Self-Supervised Learning

Creates its own labels from data.

BERT, GPT pretraining

KNN

K-Nearest Neighbors

Classifies using nearest examples.

Fruit classification

SVM

Support Vector Machine

Finds best boundary between classes.

Spam detection

DT

Decision Tree

Uses tree-like rules.

Loan approval

RF

Random Forest

Uses many decision trees.

Disease prediction

NB

Naive Bayes

Probability-based classifier.

Email spam filter

LR

Linear Regression

Predicts continuous numbers.

House price

LogR

Logistic Regression

Predicts yes/no class.

Disease yes/no

K-Means

K-Means Clustering

Groups similar data.

Customer groups

DBSCAN

Density-Based Spatial Clustering of Applications with Noise

Finds clusters and outliers.

Fraud detection

NN

Neural Network

Brain-like model that learns patterns.

Handwriting recognition

ANN

Artificial Neural Network

Basic neural network model.

Classification

DNN

Deep Neural Network

Neural network with many layers.

Image recognition

CNN

Convolutional Neural Network

Best for image data.

Face detection

RNN

Recurrent Neural Network

Best for sequence data.

Text prediction

LSTM

Long Short-Term Memory

Advanced RNN for long memory.

Translation

GRU

Gated Recurrent Unit

Simpler version of LSTM.

Speech recognition

AE

Autoencoder

Learns compressed representation.

Noise removal

VAE

Variational Autoencoder

Generates new data using encoding.

Image generation

GAN

Generative Adversarial Network

Generator creates fake data, Discriminator checks it.

AI-generated faces

GPT

Generative Pre-trained Transformer

Generates human-like text.

ChatGPT

LLM

Large Language Model

Big model trained on huge text data.

ChatGPT, Gemini

RAG

Retrieval-Augmented Generation

AI answers using retrieved documents.

PDF chatbot

VAE

Variational Autoencoder

Generates new data from learned patterns.

Image generation

NLP

Natural Language Processing

AI for human language.

Chatbots

BERT

Bidirectional Encoder Representations from Transformers

Understands text from both directions.

Question answering

NER

Named Entity Recognition

Finds names, places, dates, etc.

“Ali lives in Lahore”

POS

Part of Speech Tagging

Identifies noun, verb, adjective, etc.

Grammar analysis

BoW

Bag of Words

Represents text by word count.

Text classification

TF-IDF

Term Frequency–Inverse Document Frequency

Finds important words in text.

Search engines

HMM

Hidden Markov Model

Used for sequence prediction.

Speech recognition

CRF

Conditional Random Field

Used for sequence labeling.

Named entity recognition

ASR

Automatic Speech Recognition

Converts speech into text.

Voice typing

TTS

Text-to-Speech

Converts text into voice.

AI voice reader

STT

Speech-to-Text

Same as ASR.

Dictation app

CV

Computer Vision

AI for images and videos.

Object detection

OCR

Optical Character Recognition

Reads text from images.

Scanned documents

CNN

Convolutional Neural Network

Main model for image tasks.

Face recognition

YOLO

You Only Look Once

Fast object detection model.

Detecting cars/people

RCNN

Region-Based CNN

Object detection model.

Detecting objects in images

MSE

Mean Squared Error

Average squared prediction error.

Regression error

MAE

Mean Absolute Error

Average absolute prediction error.

House price error

RMSE

Root Mean Squared Error

Square root of MSE.

Forecast error

R²

R-Squared

Shows how well model explains data.

Regression accuracy

CE

Cross Entropy

Loss for classification.

Image classification

BCE

Binary Cross Entropy

Loss for two-class problems.

Spam / not spam

Acc

Accuracy

Correct predictions out of total.

Test accuracy

F1

F1 Score

Balance of precision and recall.

Medical detection

AUC

Area Under Curve

Measures classification performance.

Fraud detection

GD

Gradient Descent

Reduces model error step by step.

Training ML model

SGD

Stochastic Gradient Descent

Faster version of gradient descent.

Deep learning training

LR

Learning Rate

Step size during training.

Model optimization

ReLU

Rectified Linear Unit

Activation function.

CNN hidden layers

BP

Backpropagation

Updates neural network weights.

Training ANN

RLHF

Reinforcement Learning from Human Feedback

Improves AI using human feedback.

Chatbot improvement

PCA

Principal Component Analysis

Reduces number of features.

Image compression

EDA

Exploratory Data Analysis

Understanding data before modeling.

Finding trends

FE

Feature Engineering

Creating useful input features.

Age group from age

ETL

Extract, Transform, Load

Data preparation process.

Data warehouse

API

Application Programming Interface

Connects software with AI model.

Using ChatGPT in app