Довідник IT технологій — Data Science — Довідник по Machine Learning

ACID Transactions

Activation Functions

Active Learning in Machine Learning

Adaptive Gradient Algorithm (AdaGrad)

Adversarial Machine Learning

AI Center of Excellence (AI CoE)

AI Data Labeling

AI Fairness

AI Model Validation

AI Observability

Anomaly Detection

Artificial Neural Network

Attribute

Auto-Encoder

Automated Machine Learning

AutoML

Autoregressive Model

Average Precision

Backpropagation

Backpropagation Algorithm

Bagging in Machine Learning

Baseline Models

Batch Normalization

Bayes Theorem for Machine Learning

BERT

Bias-variance Tradeoff

Binary Classification

Binomial Distribution

Black Box Model

BLEU

Calibration Curve

Canonical Schema

Catastrophic Forgetting

CatBoost

Categorical Variables

CI/CD for Machine Learning

Class Imbalance

Classification Threshold

Clustering algorithms

Clustering in Machine Learning

Complex Event Processing

Computer Vision

Confusion Matrix in Machine Learning

Continuous Integration Model

Continuous Validation

Conversational Agent

Convex Optimization

Convolutional Neural Network

Cross-Validation Modeling

Data Augmentation

Data Cleaning

Data Decomposition

Data Granularity

Data Mart

Data Science Platform

Data Science Techniques

Data Science Tools

Data Vault

Data Versioning

Data Visualizations

Data-Centric AI

Datasets and Machine Learning

Decision Boundary

Decision Intelligence

Decision Tree

Decision Tree in Machine Learning

Deep Belief Networks

Deep Learning

Deep Learning Algorithms

Deep Reinforcement Learning

Degradation Model

DenseNet

Density-Based Clustering

Dimensionality Reduction

Dplyr

Drift monitoring

Early Stopping

EDA – Exploratory data analysis OR Exploration

Ensemble Learning

Enterprise Generative AI

Epoch in Machine Learning

Ethical AI

ETL Pipeline

Evolutionary Algorithms

Explainable AI (XAI)

F-score

Facial Recognition

Failure Analysis Machine Learning

False Positive Rate

Feature Engineering

Feature Selection

Feature Vector

Federated Learning

Feedback Loop

Folium

Gaussian Distribution

Gaussian Mixture Model

Generalized Linear Models

Generative Adversarial Network

Gradient boosting

Gradient Descent For Machine Learning

Grid Search

Ground Truth

Handling Outliers

Hash tables

Holdout Data

Human in the Loop Machine Learning

Hyperparameter Optimization

Hyperplane

Image Data Collection

ImageDataGenerator

Imbalanced Data

Independent and Identically Distributed Data (IDD)

Intelligent Document Processing

K-Nearest Neighbor

Keras

KNN Models

KYC Process

Learning Rate in Machine Learning

LightGBM

Linear Regression

LLM Agents

LLM Evaluation

LLM Parameters

LLM Summarization

LLMOps

LLMs Hallucinations

Local Interpretable Model-Agnostic Explanations (LIME)

Logistic Regression

Long Short-Term Memory (LSTM)

Low-Rank Adaptation of Large Language Models

Machine Learning

Machine Learning Algorithm

Machine Learning as a Service (MLaaS)

Machine Learning Bias

Machine Learning Checkpointing

Machine Learning in Software Testing

Machine Learning Inference

Machine Learning Lifecycle

Machine Learning Model Accuracy

Machine Learning Model Deployment

Machine Learning Model Evaluation

Machine Learning Pipeline

Machine Learning Workflows

Mean Absolute Error

Mean Square Error (MSE)

Meta-Learning

Missing Values in Time Series

ML Architecture

ML Diagnostics

ML Infrastructure

ML Interpretability

ML Model Card

ML Model Management

ML Model Validation

ML Orchestration

ML Scalability

ML Stack

MLOps

MLOps for Generative AI

MLOps Framework

MLOps Monitoring

Model Behavior

Model Calibration

Model Drift

Model Fairness

Model Monitoring

Model Observability

Model Parameters

Model Registry

Model Retraining

Model Selection

Model Tuning

Model-Based Machine Learning

Model-Driven Architecture

Multi-class Classification

Multilayer Perceptron

Naive Bayes Models

Natural Language Understanding

Neural Network Tuning

Neural Networks

No-code/Low-code ML

Noise in Machine Learning

Noisy Image

Normalization in Machine Learning

Observation ML

One-hot Encoding

Open-Source Machine Learning Monitoring

Out-of-distribution

Overfitting in Machine Learning

Pandas and Numpy

Pascal

Pattern Matching

Pattern Recognition

PCA – Principal Component Analysis

Pooling Layers in CNN

Precision in Machine Learning

Predictive Model Validation

Preprocessing

Probabilistic classification

Prompt Engineering

Prototype Model

PyTorch

Random Forests

Random Initialization

Recall in Machine Learning

Rectified Linear Unit (ReLU)

Recurrent Neural Network

Regression

Regression Algorithms

Regularization Algorithms

Regularization in Machine Learning

Reinforcement Learning

Reproducible AI

ResNet

Responsible AI

Ridge Regression

RMSProp

Robotic Process Automation (RPA)

ROC (Receiver Operating Characteristic) Curve

Root Mean Square Error (RMSE)

Rotating Proxies

Scikit-Learn

Segmentation in Machine Learning

Selective Sampling

Semi-supervised Learning

Sensitivity and Specificity of Machine learning

Shapley Values

Six-Month Moratorium

Softmax Function

Supervised Learning

Support vector machine

Support Vector Machines

Surrogate Model

Synthetic Data

Synthetic Data Generation

Tabular Data

TensorFlow

Test Set in Machine Learning

Top-1 error rate

Training-Serving Skew

Transformer Neural Network

Transformers Models

Tree-Based Models

Triplet Loss

True Positive Rate

Type 1 Error

Type 2 Error

Underfitting in Machine Learning

Unsupervised Learning

Validation Set in Machine Learning

VGGNet

XgBoost

YOLO (object detection algorithm)

Zero-shot learning