ArntheGitHub

63-21-TP02-2022

ArnTGH

ArntheGitHub.github.io

Complete-Python-3-Bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

django-crash-starter

django3-password-generator

django3-personal-portfolio-project

Ecommerce-Company-assignment

The company hired us to help them analize the data they have and gain valuable information to improve and increase the sales.

Fraud-Detection-in-Retail-W6

The aim of the analysis is to use the data set of 300,000 cases (W06_training.txt) to train a model that is suitable for detecting fraud attempts. The prediction of the model is finally checked with the help of another data set with 100,000 purchases for which we do not know the target variable. This data set (W06_scoring.txt) is used to evaluate how well the model’s prediction works, using the total cost or total revenue. This means that we must ensure that there is no overfitting when training the model, otherwise the prediction on the new data set will give poor results. To do this, we should split the data set into training and test data or use a suitable cross-validation method to avoid overfitting.

learning-log-

learning log

ArntheGitHub/63-21-TP02-2022

ArntheGitHub/ArnTGH

ArntheGitHub/ArntheGitHub.github.io

ArntheGitHub/Complete-Python-3-Bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

ArntheGitHub/django-crash-starter

ArntheGitHub/django3-password-generator

ArntheGitHub/django3-personal-portfolio-project

ArntheGitHub/Ecommerce-Company-assignment

The company hired us to help them analize the data they have and gain valuable information to improve and increase the sales.

ArntheGitHub/Fraud-Detection-in-Retail-W6

The aim of the analysis is to use the data set of 300,000 cases (W06_training.txt) to train a model that is suitable for detecting fraud attempts. The prediction of the model is finally checked with the help of another data set with 100,000 purchases for which we do not know the target variable. This data set (W06_scoring.txt) is used to evaluate how well the model’s prediction works, using the total cost or total revenue. This means that we must ensure that there is no overfitting when training the model, otherwise the prediction on the new data set will give poor results. To do this, we should split the data set into training and test data or use a suitable cross-validation method to avoid overfitting.

ArntheGitHub/learning-log-

learning log

ArntheGitHub/Linear-Regression-Project-Weather-Prediction-

Linear Regression project with Ridge and Lasso Regression.

ArntheGitHub/Market-Basket-Analysis

The manager of a grocery store asked for my help regarding the shelf layout of the shop. Until recently they had about 200 SKUs (stock keeping units: unique item numbers), but the headquarter of the grocery chain advised them to keep only 105 of them and introduce 64 new SKUs. The store manager is in charge of where to place those items. The 105 existing items were distributed evenly across the 7 shelves. In general everything can be changed, but the store manager suggests to keep those 105 items at their current position, unless there are very strong reasons for an alternative. Otherwise the customers could be even more confused than they will be anyway due to the change. I have been given sales data from a different shop that made the transition last year. The layout of this shop is somewhat different, but i can get from the data, which items were purchased together and which not. My task is to perform smart analysis with the data using Python code and come up with a good recommendation for the store manager. The Data set contains: 9835 rows Each row is a transaction (customer basket) The items purchased in each row are separated by commas 169 unique items

ArntheGitHub/myblog-

This is my first blog with Python&Django

ArntheGitHub/password-generator

password generator

ArntheGitHub/pcc

Resources for Python Crash Course, from No Starch Press.

ArntheGitHub/pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

ArntheGitHub/CIP-HSLU

ArntheGitHub/Data-Science-In-Healthcare

This is our Data Science in Healthcare project from the HSLU

ArntheGitHub/Data-Warehouse-Data-Lake-system-HSLU

ArntheGitHub/E-learning-

E-learning platform with (CMS) Content Management System, API and Chart Server

ArntheGitHub/ML1_HSLU

ArntheGitHub/R-Bootcamp-Project-HSLU

This is my R Bootcamp Project with Sandro