Python Programming Technologies — SPbU

Educational repository with Python and Machine Learning assignments.

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📂 Assignments Overview

1. Exploratory & Visual Data Analysis (Titanic)

• Exploratory and visual data analysis

• Handling missing and categorical data

  • titanic_eda.pdf
  • titanic_vda.pdf

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2. KNN & KD-Tree (from scratch)

• KD-Tree implementation

• KNN classifier without sklearn

  • cancer.pdf
  • spam.pdf

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3. Linear Regression

• Linear Regression (analytical solution)

• Model interpretation and error analysis

  • linreg.pdf

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4. Gradient Descent

• Linear Regression optimized with Gradient Descent

• Convergence and learning rate analysis

  • gradient_descent.pdf

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5. Support Vector Machines

• Support Vector Machines (SVM)

• Linear and kernel-based decision boundaries

  • svm.pdf

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6. Ensemble Methods

• Bagging

• Random Forest (using sklearn)

  • ensembles.pdf

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7. Clustering

• K-Means clustering

• Cluster quality metrics

  • clustering.pdf

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8. Text Analysis

• Bag-of-Words and TF-IDF

• Classical text classification approaches

  • texts.pdf

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Educational repository used as a portfolio project.