Each folder in this Repository links to a Project which I completed under GCD Program.

1. 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:

   1. Pandas -- For Data Processing.
   2. Matplotib & Seaborn -- To Visualize the results.

For More details please refer Summer_Olympics_EDA.pptx file.

2. 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 except SalePrice column which is not available in test.csv file, We have build and train a Machine Learning Model with the datas from train.csv and we need to the house price for datas in test.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:

   1. Pandas -- For Data Processing.
   2. Matplotib & Seaborn -- To Visualize the results.
   3. Scikit Learn -- To import the Machine Learning Algorthims

   I have applied the Machine Learning Algorthims to complete this project.

   1. Linera Regression
   2. XGBoost
   3. Random Forest(Ensemble)

For more details, please refer House price prediction_Recordings.pptx file.