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To start, let’s talk about the problem we’re addressing. For many startup participants and small product owners, it’s challenging to project the value and growth potential of their products. The ability to forecast sales accurately is crucial for making informed business decisions and strategic planning.

Our solution to this challenge is the Sales Forecaster. This tool leverages advanced machine learning techniques to predict future sales based on historical data. By analyzing 6 months’ worth of data, along with the product’s price, our AI can forecast the sales for the upcoming months.

We used React js. for the front end which was easy and accessible too use and made a user friendly interface to give an easy time for the user. Sales predictions will be displayed clearly, making it easy to understand and act upon the insights provided with a sleek modern look. Which once again shows that our model is very user friendly. We utilized Linear Regression and Mean Squared Error as key algorithms in the backend for our sales forecasting model. We gathered and cleaned 6 months of sales data to ensure accuracy. Handling missing values and outliers was a crucial step. Linear Regression was chosen for its simplicity and effectiveness in predicting continuous values. Mean Squared Error was used to evaluate the performance and accuracy of our model.he model was trained on historical data and rigorously tested to refine its predictions and handle different sales patterns effectively.

What makes our project unique? The AI Sales Forecaster isn’t just about predicting numbers; it’s about empowering small product owners with actionable insights. By providing accurate sales forecasts, our tool helps users make data-driven decisions, optimize their strategies, and ultimately drive growth. This can be a game-changer for startups trying to navigate uncertain markets.

Our goal is to have a proper working model of our idea by the end of the summer and publish a website that is free to use.