Learn how to build sales forecasting models using Time Series, ARIMA, SARIMA, LightGBM, Random Forest, and LSTM
Sub Category
- Data Science
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Objectives
- Learn how to build sales forecasting model using ARIMA, SARIMA, LightGBM, Random Forest, and LSTM
- Learn how to conduct customer segmentation analysis
- Learn how to analyze sales performance trend
- Learn how to evaluate forecasting model’s accuracy and performance by calculating mean absolute error and conduct residual analysis
- Learn how time series forecasting model work. This section will cover data collection, preprocessing, train test split, model selection, and model training
- Learn about factors that can contribute to sales performance, such as seasonal trends, market saturation and supply chain efficiency
- Learn how to find and download datasets from Kaggle
- Learn how to clean dataset by removing missing rows and duplicate values
- Learn how to analyze order fulfilment efficiency
- Learn the basic fundamentals of sales forecasting
Pre Requisites
- No previous experience in sales forecasting is required
- Basic knowledge in Python and statistics
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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