well, firstly i was keen to build a strong resume and data science is my interest topic too. so i thought i can not fail without trying and giving it a shot atleat and there i am proudly saying that i'm a level up in data science analysis.
What it does
The aim is to build a predictive model and find out the sales of each product at a particular store. Using this model, we will try to understand the properties of products and stores which play a key role in increasing sales.
How I built it
Data Summary: Exploration, Viualization, Data Imputation Preprocessing / Feature Engineering: Deriving the column, Transfomation, FEature selection Dividing our data interms of trainig and testing Building the model: linear regression, Ensemble regressor methods
Challenges I ran into
7+ Models === the less rmse will be chosen for deployment. choosing a model for data analysis
Accomplishments that I'm proud of
my first ever hackathon submission and i have learnt a lot :)
What I learned
bi data analysis using python. how to use jupyter notebook and anaconda cloud base
What's next for largeDataSales
still need to explore