- Predictive modeling (forecasting, risk analysis, outcome prediction)
- Classification and clustering (SVM, decision trees, random forests, k-means)
- Deep learning (CNNs, RNNs, transformers)
- Natural Language Processing (text mining, sentiment analysis, entity recognition)
- Recommendation systems
- Time-series forecasting
- Data visualization and publication-ready reporting
Your project will be handled by Pubrica’s team of data scientists, AI engineers, and ML experts, with proven experience across 100+ ML projects in healthcare, life sciences, and business analytics.
We use industry-leading frameworks and tools such as Python, R, TensorFlow, PyTorch, Scikit-learn, Keras, SQL, Tableau, and Power BI. For cloud-based solutions, we leverage AWS, Azure ML, and Google Cloud AI.
Yes. Our team is skilled in managing small, large, and complex datasets, including structured, semi-structured, and unstructured data such as text, images, and clinical records.
Absolutely. We design custom ML models tailored to your objectives, whether it’s healthcare analytics, academic research, or business intelligence, ensuring relevance, accuracy, and cost-effectiveness.
Yes. We encourage regular communication through email, virtual meetings, and chat, so you can stay updated, review progress, and provide feedback at every stage of the ML workflow.

















