Berkan Sesen (@berkansesen)

Handling Class Imbalance: Downsampling, SMOTE, and Beyond

Compare five strategies for imbalanced classification: random downsampling, upsampling, SMOTE, and class weights. Evaluate with precision-recall curves and F1, not just accuracy.

13 min readsesenai.hashnode.dev

Jul 5

AIC and BIC: Choosing the Right Model Without Overfitting

Derive the log-likelihood from first principles, then build AIC and BIC as penalised model selection criteria. Compare polynomial fits, visualise the bias-variance tradeoff, and understand when to use each criterion.

13 min readsesenai.hashnode.dev

Jun 29

Trust Region Methods: From REINFORCE to TRPO to PPO

Implement REINFORCE, TRPO, and PPO from scratch in PyTorch on CartPole. Understand why vanilla policy gradients are unstable, how trust regions fix it, and why PPO became the default algorithm in modern RL.

21 min readsesenai.hashnode.dev

Jun 17

LDA vs PCA: Supervised Meets Unsupervised Dimensionality Reduction

Compare PCA and Fisher's Linear Discriminant Analysis on the Iris dataset. Learn when unsupervised reduction fails, why labels matter, and the eigenvalue problem behind both methods.

13 min readsesenai.hashnode.dev

Jun 12

Changepoint Detection: Finding Regime Shifts in Financial Data

Detect volatility regime shifts in the S&P 500 using the PELT algorithm in Python. Compare PELT with Binary Segmentation, tune the penalty parameter, and align detected changepoints with real financial crises.

14 min readsesenai.hashnode.dev

Jun 9

Berkan Sesen

About

Available for

Berkan Sesen's blogs

Handling Class Imbalance: Downsampling, SMOTE, and Beyond

AIC and BIC: Choosing the Right Model Without Overfitting

Trust Region Methods: From REINFORCE to TRPO to PPO

LDA vs PCA: Supervised Meets Unsupervised Dimensionality Reduction

Changepoint Detection: Finding Regime Shifts in Financial Data

Berkan Sesen

About

Available for

Berkan Sesen's blogs

Handling Class Imbalance: Downsampling, SMOTE, and Beyond

AIC and BIC: Choosing the Right Model Without Overfitting

Trust Region Methods: From REINFORCE to TRPO to PPO

LDA vs PCA: Supervised Meets Unsupervised Dimensionality Reduction

Changepoint Detection: Finding Regime Shifts in Financial Data

Berkan Sesen

About

Available for

Berkan Sesen's blogs

Handling Class Imbalance: Downsampling, SMOTE, and Beyond

AIC and BIC: Choosing the Right Model Without Overfitting

Trust Region Methods: From REINFORCE to TRPO to PPO

LDA vs PCA: Supervised Meets Unsupervised Dimensionality Reduction

Changepoint Detection: Finding Regime Shifts in Financial Data

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Berkan Sesen

About

Available for

Berkan Sesen's blogs

Handling Class Imbalance: Downsampling, SMOTE, and Beyond

AIC and BIC: Choosing the Right Model Without Overfitting

Trust Region Methods: From REINFORCE to TRPO to PPO

LDA vs PCA: Supervised Meets Unsupervised Dimensionality Reduction

Changepoint Detection: Finding Regime Shifts in Financial Data