M1

Project framework

1. PROJECT OVERVIEW:
   The primary objective of the project is to determine the clients that would most likely purchase Apple’s newly released M1 Macbook.

2. DATA COLLECTION:
   The data was collected through a survey sent across different techno savvy groups over 1 week period of time.

3. DATA PREPARATION & ANALYSIS :
   Collected data is prepared by converting columns with appropriate labels. Collected data is prepared by encoding Boolean value and converting dtypes. Datasets are linearly separable using all 22 input features.

4. CORRELATION & FEATURE SELECTION :
   

• The dataset consists of multiple suitable features to predit the profile of the clients who would purchase the new Apple’s M1 Macbook.

• With the help of correlation matrix a strong relationship will be drawn between multiple feature which are then labelled and categorized as independent variable (x) used along with a target variable ‘m1_purchase’ (y) to fit a model that can predict the profiles of the clients who would likely purchse the new Apple’s M1 Macbook.

5. MODEL CHOISE:
   A Support Vector Machine (SVM) will be used in this notebook as SVM is a very powerful and versatile Machine Learning model, capable of performing linear or nonliner classification, regression, and even outlier detection from the scikit-learn package.