Each folder in this Repository links to a Project which I completed under GCD Program.
-
Term1&2 EDA Project : In this Project i have analayzed a Summer Olympics data provided by INSAID and in that I have analyzed many parameters and found the relations among them. I have used the below libraries from Python to complete the project.
Tools Used:
- Pandas -- For Data Processing.
- Matplotib & Seaborn -- To Visualize the results.
For More details please refer Summer_Olympics_EDA.pptx
file.
-
Machine Learning Foundation : In this Project, I have Ames Housing Dataset downladed from Kaggle's Getting Started Competion. In this i have applied Machine Learning Algorithms to predict the house of given dataset. The Dataset containd 2 files names
train.csv
&test.csv
. Each has same columns exceptSalePrice
column which is not available intest.csv
file, We have build and train a Machine Learning Model with the datas fromtrain.csv
and we need to the house price for datas intest.csv
file, I have uses the below tools from Python to complete this project. And provided a high level relation between the parameters in a ppt file.Tools Used:
- Pandas -- For Data Processing.
- Matplotib & Seaborn -- To Visualize the results.
- Scikit Learn -- To import the Machine Learning Algorthims
I have applied the Machine Learning Algorthims to complete this project.
- Linera Regression
- XGBoost
- Random Forest(Ensemble)
For more details, please refer House price prediction_Recordings.pptx
file.