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Frustra fit per plura quod potest fieri per pauciora
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Frustra fit per plura quod potest fieri per pauciora

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  1. Machine-Learning-on-Tabular-Data Machine-Learning-on-Tabular-Data Public

    Code for the new Manning book on machine learning on tabular datasets

    Jupyter Notebook 55 16

  2. deep-learning-for-tabular-data deep-learning-for-tabular-data Public

    An updated (2025) guide to Deep Learning for tabular data, comparing a fine-tuned Keras 3 (PyTorch backend) DNN and an Optuna-optimized XGBoost model on the Kaggle Amazon Employee Access Challenge

    Jupyter Notebook 48 14

  3. Gemma-3-1B-financial-sentiment-analysis Gemma-3-1B-financial-sentiment-analysis Public

    Fine-Tuning Gemma 3 1B-IT for Financial Sentiment Analysis

    Jupyter Notebook 1

  4. Gemma-2-2B-IT-GRPO Gemma-2-2B-IT-GRPO Public

    Fine-tuning the Google/gemma-2-2b-it model using Generative Reward Post-Optimization (GRPO)

    Jupyter Notebook 13 2

  5. Gemma-3-Function-Calling Gemma-3-Function-Calling Public

    Making google/gemma-3-1b-it model ready for an agentic role with function calling tasks

    Jupyter Notebook 1

  6. kaggledays-2019-gbdt kaggledays-2019-gbdt Public

    Kaggle Days Paris - Competitive GBDT Specification and Optimization Workshop

    Jupyter Notebook 92 34