Welcome to the Sales Forecasting AI Challenge!

There are numerous advanced tools and techniques are employed for data analysis such as vision techniques, Natural Language Processing (NLP), data analytics, Internet of Things (IoT) , and many more. One of the techniques frequently preferred for analysing financial data is statistical Time Series Analysis. The ability to predict sales or prices of stock based on the current statistics is almost need of every company these days. You are required to build a model to predict sales and volume of the respective agencies mentioned in the data. You may build a single model or a cluster of models using either statistics, deep learning or other machine learning techniques.

The dataset consists of single train file "train.csv" which contains the fields "YearMonth" (Financial year), "Agency", "SKU", ..... The dataset also contains the redundant fields and NaN values that the participants have to identify. Most of the fields name are self-explanatory.

Sample Data:

Agency, SKU, YearMonth, Volume, Price, Sales, Promotions, Avg_Max_Temp

0, 22, 1, 2013-01-01, 52.27, 1168.9, 1069.17, 99.74, 25.85

1, 22, 4, 2013-01-01, 31.06, 1742.11, 1598.41, 143.7, 25.85

Data Source

Volume Forecasting: SKU future volume analysis and prediction

Akku M's Certificate

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