Retaining customers is a big challenge for companies, so predicting and reducing the churn rate by targeted offers is a common strategy. YData helps to balance, clean, and filter the data, and create processing pipelines to compare and tune different ML model hyperparameters.
Recommendation systems use advanced clustering algorithms which need a lot of data from every user profile. A good recommendation system requires the models to be fine-tuned properly, in addition to good data preprocessing, cleaning and synthesis, if required.
Predicting when customers are most likely to buy your product can boost your business multifold. Resource management and stock optimization can be done effectively by predicting the buyer sentiment for that period. YData adds to this capability by helping with data cleaning, preprocessing, synthesis, and pipeline setup for your product lines.
Synthetic data, artificially generated data that mimics real-world data, is a technology that has undergone significant transformation in recent years. Since the dawn of data-driven synthetic data generation with generative models,...
Photo by Roman Kraft on Unsplash As machine learning continues to evolve, the use of Large Language Models (LLMs) has become increasingly prevalent, particularly in complex tasks requiring deep understanding and generation of human-like...
Photo by Isaac Smith on Unsplash Synthetic data bootstrap In the dynamic landscape of organizations high-quality data is a requirement for the development of many solutions - from software testing and validation all the way to Artificial...
