Models

Linear Regression

Logistic Regression

Softmax Regression

Support Vector Machines (SVM)

Decision Trees (DT)

Random Forests

Neural Network (NN)

k-Nearest Neighbors (k-NN)

K-Means Clustering

Transformers

Gradient Boosting

Naive Bayes

ML Concepts

MLOps

Types of ML

Bias-Variance tradeoff

Regularization

Hyperparameters

Curse of Dimensionality

Feature Engineering

Gradient Descent

Backpropagation

Cross-validation

Explainability and Interpretability

One-Hot Encoding

Ensemble Learning

ML tasks

Statistical Concepts

Principal Component Analysis (PCA)

Maximum Likelihood Estimation (MLE)

Hypothesis Testing

A/B Testing

Central Limit Theorem

Confidence Interval

Correlation

Variance and Covariance

Miscellaneous

Resources

Ideas

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