• Stars
    star
    1
  • Language
  • Created about 4 years ago
  • Updated about 4 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

More Repositories

1

Dragon-Real-Estate---Price-Predictor

Jupyter Notebook
3
star
2

Insurance-Claims-Case-Study

Jupyter Notebook
2
star
3

shashvindu

Jupyter Notebook
2
star
4

Data-Visualization-Case-Study-in-Python

Jupyter Notebook
2
star
5

predicting-credit-spend-identifying-key-drivers2

Jupyter Notebook
1
star
6

basic-stats--case-study-2

Jupyter Notebook
1
star
7

pdftotable

Jupyter Notebook
1
star
8

Segmentation-of-Credit-Card-Customers

Jupyter Notebook
1
star
9

Linear_Regression_Case_R

R
1
star
10

R-case-study-2-Credit-card-

R
1
star
11

video_audio_text

Jupyter Notebook
1
star
12

spamclassifer

Jupyter Notebook
1
star
13

dl_keras_MNIST-digits-classification-dataset

1
star
14

reset-image-size-by-usging-python

Jupyter Notebook
1
star
15

dl_keras_MNIST_digits-classification-dataset

Jupyter Notebook
1
star
16

deepl_keras_fashion_mnist

Jupyter Notebook
1
star
17

sql1

1
star
18

LR---Prediction-of-Car-Sales

LR - Prediction of Car Sales
Jupyter Notebook
1
star
19

Document-Classification

Jupyter Notebook
1
star
20

Pencilsketch-opencv-by-shashvindu

Jupyter Notebook
1
star
21

R-RCASE-STUDY-3-Visualization-

1
star
22

R-CASE-STUDY-1-Retail-.Rmd

HTML
1
star
23

jhashashvindu-yahoo.com-CREDIT-CARD

Jupyter Notebook
1
star
24

Recommendation-Engine-using-CF

Jupyter Notebook
1
star
25

Bank-Reviews-Complaints-Analysis-master

Jupyter Notebook
1
star
26

jhashashvindu-yahoo.com-basic-stats1

Jupyter Notebook
1
star
27

word2vac

Jupyter Notebook
1
star
28

sql2

1
star
29

ml-code

Jupyter Notebook
1
star
30

predicting-credit-spend-identifying-key-drivers

Business Problem: One of the global banks would like to understand what factors driving credit card spend are. The bank want use these insights to calculate credit limit. In order to solve the problem, the bank conducted survey of 5000 customers and collected data. The objective of this case study is to understand what's driving the total spend (Primary Card + Secondary card). Given the factors, predict credit limit for the new applicants Data Availability: οƒΌ Data for the case are available in xlsx format. οƒΌ The data have been provided for 5000 customers. οƒΌ Detailed data dictionary has been provided for understanding the data in the data. οƒΌ Data is encoded in the numerical format to reduce the size of the data however some of the variables are categorical. You can find the details in the data dictionary
Jupyter Notebook
1
star
31

Pandas-Basic-Exercises-10-Exercises-

Jupyter Notebook
1
star