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Recruiter's Glossary

Examples: t-SNE • PCA • Bias-Variance

Machine Learning Terms

Understanding these terms will help you better evaluate candidates and communicate with hiring managers

Hyperparameter Tuning

MLflow

Feature Selection

Batch Learning

SciPy

Regularization

Pipeline Orchestration

DVC

Collaborative Filtering

Scikit-learn

F1 Score

PCA

Bias-Variance

Cross-Validation

XGBoost

Model Interpretability

Feature Store

Precision-Recall

Bagging

Bayesian Optimization

Time Series Analysis

Data Drift

CatBoost

Model Versioning

A/B Testing

Recommendation Systems

Pandas

AUC

NumPy

Matrix Factorization

UMAP

Dimensionality Reduction

ROC Curve

Dropout

Batch Normalization

Model Registry

LightGBM

Random Search

Anomaly Detection

Online Learning

Overfitting

Kubeflow

Confusion Matrix

Weight & Biases

Ensemble Methods

MLOps

Grid Search

Underfitting

Boosting

t-SNE

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