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data-science-portfolio's Introduction

Data Science Portfolio

1. Classification

  • Classification-Decision-Trees.ipynb
  • Classification-Logistic-Regression.ipynb
  • Classification-SVM-cancer.ipynb

2. Clustering

  • Clustering-K-Nearest-neighbors.ipynb
  • Clustering-Hierarchical-Cars.ipynb
  • Clustering-K-Means.ipynb

3. Data Wrangling

  • Data-wrangling-using-Python.ipynb

4. Feature Selection & Exploratory Data Analysis

  • Exploratory study on feature selection.ipynb
  • Full_Exploratory-data-analysis.ipynb

5. Model Evaluation

  • Model-Evaluation-and-refinement.ipynb

6. Plots_Charts

  • Area-Plots-Histograms-and-Bar-Chart.ipynb
  • Introduction-to-Matplotlib-and-Line.ipynb
  • Plots-using-Matplotlib.ipynb
  • Pie-Charts-Box-Plots-Scatter-Plots.ipynb
  • WaffleCharts-WordClouds-and-Regres

7. Python

  • Classes-In-Python.ipynb
  • Functions-in-Python.ipynb
  • Intro_API_and_RestAPI.ipynb
  • Python-WriteFile.ipynb

8. Recommendation

  • Collaborative-Filtering-movies.ipynb
  • Recommendations-sys-content-based.ipynb

9. Regression

  • Linear-Regression.ipynb
  • Mulitple-Linear-Regression.ipynb
  • Polynomial-Regression.ipynb
  • Regression-NoneLinear.ipynb
  • Regresssion-Simple_&_Multiple-Analysis.ipynb

10. Miscellaneous

  • Speech-To-Text-Conversion.ipynb
  • CropImage.ipynb
  • Image Processing.ipynb
  • Numpy-1D.ipynb

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