Custom CNN Architecture for Real vs. Spoof Detection

results = {
    "validation_accuracy": "99.39%",
    "test_accuracy": "99.29%",
    "dataset_size": "38K images",
    "parameters": "4.88M"
}

• Built SpoofNet from scratch with BatchNorm, Dropout2D, AdaptiveAvgPooling
• Real-time inference with MediaPipe + OpenCV on GPU
• Automated face extraction pipeline with quality filters
• Production-ready with only 2 false negatives, 40 false positives

Tech: PyTorch • OpenCV • MediaPipe • Gradio

Parameter-Efficient Transformer Fine-Tuning

efficiency = {
    "parameter_reduction": "99.87%",
    "trainable_params": "147K vs 110M",
    "accuracy": "91.74%",
    "speedup": "750x faster training"
}

• Custom LoRA implementation with rank-4 low-rank matrices
• Injected into Q/V projections across 12 BERT encoder layers
• Built end-to-end pipeline with HuggingFace Transformers
• Optimized with AdamW + gradient freezing

Tech: PyTorch • HuggingFace • LoRA • SST-2

Bidirectional Sequence Modeling for IMDB Reviews

performance = {
    "test_accuracy": "85.19%",
    "train_test_gap": "4%",
    "architecture": "2-layer BiLSTM",
    "embedding_dim": 128
}

• Bidirectional LSTM with 50% dropout for regularization
• Gradient clipping (max norm=1.0) for stable training
• Gradio deployment for real-time inference
• Handles sequences up to 256 tokens with OOV support

Tech: PyTorch • LSTM • Gradio • NLP

Classical ML with Advanced Feature Engineering

model_comparison = {
    "Random_Forest": "97.2%",
    "Logistic_Regression": "96.5%",
    "SVM": "95.8%",
    "after_tuning": "+1-2%"
}

• Comprehensive EDA with correlation heatmaps and PCA
• GridSearchCV hyperparameter optimization
• Multi-class classification on 178 samples, 13 features
• Full evaluation with confusion matrices & classification reports

Tech: scikit-learn • Pandas • Matplotlib • NumPy

#7831 • Fix ValueError in train_test_split with NumPy 2.0+

Resolved compatibility issue with NumPy 2.0+ by wrapping stratify column array access with np.asarray(). Maintains backward compatibility with NumPy 1.x while fixing array copy errors.

bug-fix compatibility numpy

#7648 • Fix misleading docstring examples across multiple methods

Updated docstrings for add_column(), select_columns(), select(), filter(), shard(), and flatten() to clarify that these methods return new datasets instead of modifying in-place. Significantly improves API documentation clarity.

documentation api-improvement datasets

#7623 • Fix: Raise error when data_dir and data_files are missing

Added validation check in FolderBasedBuilder to prevent silent fallback to current directory when loading folder-based datasets without required parameters. Improves user experience by catching errors early.

bug-fix validation datasets

#3223 • Add support for Date features in Croissant schema

Implemented support for Date, UTCDate, and UTCTime features in Croissant schema generation. Automatically infers correct dataType (sc:Date, sc:Time, or sc:DateTime) based on format string.

feature croissant schema

#3219 • Refactor: Replace get_empty_str_list with CONSTANT.copy

Eliminated shared mutable default values in dataclass fields by replacing helper functions with explicit constant copies. Makes configuration behavior more explicit and prevents subtle bugs.

refactor best-practices config

#3218 • Test: Add unit tests for get_previous_step_or_raise

Implemented comprehensive unit tests for cache retrieval function covering successful cache hits, missing cache scenarios, and error status handling. Improves code coverage and reliability.

testing unit-tests coverage

#3206 • Refactor: Use HfApi.update_repo_settings for gated datasets

Removed redundant custom implementations of update_repo_settings() across test utilities by leveraging official huggingface_hub API. Cleaned up 222 lines of code while maintaining full functionality.

refactor code-cleanup testing