numpy

Table of Contents Introduction Data Quality Analysis Loans Customers Segmentation Law 26.951 Results Presence of Missing Values in the Dataset Presence of Missing Values in the Dataset Low Success Rate in Marketing Campaigns Risk of Default Among Borrowers Non-Compliance with Law 26.951 Introduction Language used: Python Libraries used Library Description pandas Data manipulation and analysis to work with structured data numpy For numerical operations to work on large and multi-dimensional arrays and matrices matplotlib....

Table of Contents Introduction Data Wrangling Model Introduction Language used: Python Goal: Prediction of house prices. Data used: Dataset from Properati website (https://www.properati.com.ar/). Two datasets: one for training (dataframe: dfef) and one for testing (dataframe: dfp) Link to the Dataset: https://www.kaggle.com/datasets/jluza92/argentina-properati-listings-dataset-20202021/data (1gb) Libraries used Library Description pandas Data manipulation and analysis to work with structured data numpy For numerical operations to work on large and multi-dimensional arrays and matrices sklearn used for machine learning algorithms for classification, regression, clustering, dimensionality reduction matplotlib....