SaleFore AI: Ultra-accurate sales forecasting using ensemble ML (XGBoost, LightGBM, CatBoost) with RTX 4060 GPU optimization. Achieves 88-95% accuracy with advanced hyperparameter tuning.
-
Updated
Aug 22, 2025 - Python
#
optuna-optimization
Here are 26 public repositories matching this topic...
Language: All
Filter by language
Sort: Most stars
Sort options
Understanding menstruation and cycle length using clustering, predictive modeling and model interpretability
clustering supervised-learning predictive-modeling unsupervised-learning interpretability menstruation-cycle explainability optuna-optimization
-
Updated
Oct 3, 2025 - Jupyter Notebook
A reinforcement learning trading agent that uses Proximal Policy Optimization (PPO) with automated hyperparameter tuning via Optuna to learn optimal trading strategies.
education stock-trading proximal-policy-optimization reinforcement-learning-agent optuna-optimization
-
Updated
Aug 10, 2025 - Jupyter Notebook
rsna_pneumonia_project
deep-learning scikit-learn pytorch pyhton pydicom tqdm torchvision pneumonia-detection gradcam-visualization optuna-optimization
-
Updated
Oct 20, 2025 - Jupyter Notebook
Banking_ML_Project
-
Updated
Sep 5, 2025 - Jupyter Notebook
Hourly Energy Consumption
deep-learning time-series tensorflow lstm-neural-network prophet-model sarimax-model optuna-optimization
-
Updated
Sep 5, 2025 - Jupyter Notebook
2024 한국인공지능융합기술학회 추계학술대회에 제출한 논문에 대한 연구 내용입니다.
-
Updated
Sep 21, 2025 - Jupyter Notebook
Predicting telco customer churn with deep learning and advanced feature engineering on the Telco Customer Churn dataset.
deep-learning exploratory-data-analysis eda churn-prediction exploratory-data-visualizations optuna-optimization
-
Updated
Sep 2, 2025 - Jupyter Notebook
Création d'un pipeline pour prévoir la consommation électrique d'une presse à balle
-
Updated
Oct 7, 2025 - Jupyter Notebook
This repository contains a comprehensive deep learning solution for Alzheimer's Disease Classification using state-of-the-art DenseNet architectures optimized with Optuna hyperparameter tuning. The project implements multiple DenseNet variants for classification of Alzheimer's disease stages from brain MRI images.
computer-vision deep-learning tensorflow keras neuroimaging transfer-learning hyperparameter-tuning medical-image-analysis densenet121 densenet169 medical-ai streamlit-webapp densenet201 brain-mri-classification alzheimer-disease-classification alzheimer-detection optuna-optimization adni-dataset
-
Updated
Jun 19, 2025 - Jupyter Notebook
The final structure of my thesis project (notebooks and files still needs some polishing).
jupyter-notebook generative-adversarial-network predictive-maintenance tabgan wgan-gp-pytorch ai4i2020 optuna-optimization
-
Updated
Aug 28, 2025 - Jupyter Notebook
Kaggle Playground Series - Season 5, Episode 7
machine-learning kaggle-competition classification pyhton preprocessing catboost-classifier personality-type optuna-optimization
-
Updated
Jul 16, 2025 - Python
Kaggle Playground Series - Season 5, Episode 5
python data-science machine-learning data-visualization kaggle kaggle-competition optuna-optimization
-
Updated
Jun 25, 2025 - Python
Leveraging XGBoost to predict whether a customer will subscribe to a bank's term deposit
data-science machine-learning banking xgboost binary-classification xgboost-classifier optuna-optimization
-
Updated
Aug 25, 2025 - Jupyter Notebook
AI-powered anemia detection with classical ML, refined datasets, and explainable predictions using SHAP.
-
Updated
Oct 18, 2025 - Jupyter Notebook
This project was developed for the ML Engineering Postgraduate Program, where a classification machine learning model was built to predict whether a customer will subscribe to a term deposit after a marketing campaign.
data-science machine-learning machine-learning-algorithms jupyter-notebook lightgbm machinelearning uv classification-model machine-learning-projects fastapi optuna bank-marketing-dataset streamlit optuna-optimization
-
Updated
Sep 29, 2025 - Jupyter Notebook
Loan default prediction notebook using traditional machine learning models and LightGBM. Tackling imbalanced financial data and evaluating performance with ROC-AUC.
scikitlearn-machine-learning loan-default-prediction lightgbm-models smote-sampling optuna-optimization
-
Updated
Aug 30, 2025 - Jupyter Notebook
A curated collection of machine learning and deep learning notebooks — classification, regression, CV, autoencoders, NLP, and time series forecasting with TensorFlow, PyTorch, and Ray Tune.
nlp machine-learning computer-vision deep-learning tensorflow scikit-learn keras jupyter-notebook regression pytorch lstm classification autoencoder transfer-learning hyperparameter-tuning ray-tune optuna-optimization
-
Updated
Oct 7, 2025 - Jupyter Notebook
A modular AutoML framework for text classification using the IMDB dataset. The project compares CNN and RNN architectures for sentiment analysis and leverages Optuna for hyperparameter optimization. Built with TensorFlow/Keras, the pipeline is designed to be reusable, and extensible.
-
Updated
Aug 29, 2025 - Python
This project implements a **Handwritten Digit Classification** system using the **MNIST dataset**. The model is trained to recognize digits from `0–9` based on grayscale images of handwritten characters. The project demonstrates the application of deep learning techniques for image recognition tasks.
-
Updated
Sep 16, 2025 - Jupyter Notebook
Improve this page
Add a description, image, and links to the optuna-optimization topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the optuna-optimization topic, visit your repo's landing page and select "manage topics."