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Independent Projects and Competition Submissions on Data Science, Machine and Deep Learning

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Data Science

Independent Projects and Competition Submissions on Data Science, Machine and Deep Learning

  1. Titanic Survival Prediction - Kaggle Link

    • Position: Top 33% [78% Accuracy]
    • Model: Random Forest (/w Parameter gridsearch)
    • Data Preprocessing: Missing values and outliers removal (cleaning), replaced age data to categorical bins
  2. MNIST Digit Recognizer - Kaggle Link

    • Position: Top 18% [94.5% Accuracy] (91% without data augmentation)
    • Model: CNN (Modified LeNet, 2Conv, 2FC)
    • Data Preprocessing: Normalization and Data Augmentation (Translate and Rotate-Crop)
    • Optimizer: SGD + momentum with Step LR decay
    • Regularization: Dropout (0.2)
  3. CIFAR-10 Image Classification - Kaggle Link

    • Position: 81% Accuracy (74% without data augmentation)
    • Model: CNN (4 Conv, 3FC)
    • Optimizer: Adam with LR decay
    • Data Preprocessing: Normalization and Data Augmentation (Translate, Rotate and Zoom)
    • Regularization: Dropout (0.25) or BatchNormalisation [Both gave similar performance]
  4. Facial Keypoint Detection - Kaggle Link

    • Position: 2.456 (Mean Average Error)
    • Model: CNN (3 Conv, 3FC)
    • Optimizer: Adam with LR decay
    • Data Preprocessing: Normalization
    • Regularization: Dropout (0.25)

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