Feature/add neural network tasks hw2 and hw2 excellence #4
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Marcus-Vu-Code wants to merge 4 commits into
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Feature/add neural network tasks hw2 and hw2 excellence #4Marcus-Vu-Code wants to merge 4 commits into
Marcus-Vu-Code wants to merge 4 commits into
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March 10, 2026 06:55
- mlp_lvl5_ensemble_distillation: Knowledge distillation with ensemble teachers - cnn_lvl5_attention_mechanisms: SE-Net attention blocks in CNNs - nlp_lvl1_text_embedding: Skip-gram word embeddings with sentiment classification - robust_lvl1_adversarial_training: FGSM attacks and adversarial training defense All tasks follow pytorch_task_v1 protocol with: - Self-contained single task.py files - Complete required function implementations - Proper error handling and exit codes - Quality assertions and metrics - Comprehensive documentation Fixes: Homework requirement for four new neural network tasks
Add two BigQuery Bigframe NLP tasks: nlp_lvl2_bigframe_embeddings (semantic similarity with Vertex AI embeddings and local fallback) and nlp_lvl3_bigframe_llm_classification (LLM-enriched multi-class classification with augmentation and local simulation). Update MLtasks/ml_tasks.json with task metadata and requirements. Include task implementations under MLtasks/tasks/, precomputed outputs and artifact placeholders under output/, and small helper files (fix_hash.py, fix_hash2.py) plus run/temp logs (run2_task1.txt, run2_task2.txt, temp_task1.txt). Tasks implement data loading, fallback behavior, feature/embedding generation, model training/evaluation, and artifact saving (models, metrics, cache summaries).
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