Machine Learning / Multimodal AI Analysis & Forecasting

I am putting together a single, end-to-end machine-learning pipeline that can ingest three kinds of data—text, numbers, and images—and turn them into actionable insight. The heart of the project is a blend of data analysis, prediction/forecasting, and natural language processing.

I am lookng for AI specialist partners who can assist me with european based projects who are maybe in asia or americas.

For text I will supply customer reviews, social-media posts, and scientific articles. I want sentiment and topic extraction from the reviews and posts, and key-concept summarisation for the articles. On the numerical side I have time-series and tabular metrics that need feature engineering followed by forecasting. Finally, the image component involves basic classification and the option to link visual patterns back to the textual or numeric findings.

I expect clean, well-commented Python code—ideally using Pandas for preprocessing, scikit-learn or PyTorch/TensorFlow for modelling, and a Jupyter notebook that shows the full workflow from raw input to final visualised output. Package versions should be pinned in a requirements file, and every model must be serialised so I can reproduce the results later.

Deliverables
• End-to-end notebook or script for each data modality plus an orchestration file bringing them together
• Trained model files and concise README on how to rerun training and inference
• Short report highlighting performance metrics, feature importance, and any cross-modal insights

Once everything runs on my side with the same metrics you obtain, the project is complete.