Learn how to predict future sales using machine learning with a challenging time-series dataset consisting of daily sales data provided by 1C Company. Explore, analyze, train, evaluate, and make predictions with different models. Get started now!
The sale prediction is essential for a business house to enable it to produce the required quantity at the right time. It also helps in overall business planning, risk management and budgeting. Machine learning algorithms help to achieve these things in efficient way.
The aim of the project is predicts total sales for every product and store in the next month with a challenging time-series dataset consisting of daily sales data, kindly provided by one of the largest Russian software firms - 1C Company.
The dataset provided with daily historical sales data. The task is to forecast the total amount of products sold in every shop for the test set. Note that the list of shops and products slightly changes every month.
The dataset contains 6
Here's an outline of the project:
!pip install jovian --upgrade --quiet
# Execute this to save new versions of the notebook jovian.commit(project="final-ml-project")
[jovian] Detected Colab notebook... [jovian] Please enter your API key ( from https://jovian.ai/ ): API KEY: ·········· [jovian] Uploading colab notebook to Jovian... Committed successfully! https://jovian.ai/saini-9/final-ml-project