Data Analysis | Preprocessing | Visualizations

Repo contains a variety of data insights techniques for ML and analytics projects with an intermediate version including Data Analysis Notebooks + Data Visualization Notebooks + Data Pre-processing Notebooks + etc. Also few of theorotical concepts included as article mean while.

Contents

🧲 Contents in detail

• Data Preprocessing

  • Text and categorical data
  • Missing values - numerical
  • Feature scalling

• Data Visualizations

  • Matplotlib basics1
  • Plotly basics1
  • Seaboen basics1
  • Seaborn basics2

• Popular Evaluation Matrics

  • Classification Metrics (accuracy, precision, recall, F1-score, ROC, AUC, log-loss)
  • Regression Metrics (MSE, MAE, RMSE, Adj R². R²)
  • Ranking Metrics (MRR, DCG, NDCG)
  • Statistical Metrics (Correlation)
  • Computer Vision Metrics (PSNR, SSIM, IoU)
  • NLP Metrics (Perplexity, BLEU score)
  • Text Similarity Metrics (Jaccard Index, Cosine Similarity)
  • Deep Learning Related Metrics (Inception score, Frechet Inception distance)

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