I will build predictive models and forecast trends using ai and ml

You need a structured dataset in CSV, Excel, or a database format. The dataset should include historical data with relevant features that influence the target variable. If you’re unsure, I can help with data preprocessing and feature selection.

Yes. If your dataset is small, I can apply data augmentation or synthetic data techniques. For missing values, I use statistical imputation and feature engineering to improve model performance.

Absolutely. I can include a model evaluation report, visualizations, and insights at additional cost to help you understand how predictions are made and how they can be used effectively.

Supervised learning requires labeled data, but I can assist in data labeling strategies or suggest unsupervised learning techniques if labeling is not feasible.

Typically, the more historical data available, the better the forecast accuracy. However, I can work with as little as 24-36 months of data and apply data augmentation techniques if needed.

Yes, I can build multi-category or hierarchical forecasting models for sales, demand, financial trends, and inventory planning across multiple products, stores, or time periods.

Yes, I incorporate seasonality, holidays, and external variables into the forecasting model when relevant. Facebook Prophet, for example, is well-suited for handling these effects.

I use industry-standard metrics such as MAE, RMSE, MAPE, and R² to evaluate forecast accuracy. I provide a detailed model performance report with all forecasts.