GithubHelp home page GithubHelp logo

Arnold Olympio's Projects

e-learning- icon e-learning-

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

ecommerce-company-assignment icon 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 icon 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 modelโ€™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.

market-basket-analysis icon 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

myblog- icon myblog-

This is my first blog with Python&Django

pcc icon pcc

Resources for Python Crash Course, from No Starch Press.

pydata-book icon pydata-book

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

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.