ab-testing-ecommerce

Analyze A/B Testing. For this project, you will be working to understand the results of an A/B test run by an e-commerce website. Your goal is to work through this notebook to help the company understand if they should implement the new page, keep the old page, or perhaps run the experiment longer to make their decision.

advertising-ab-testing

is about advertising agency want to test whether show different type of ad will affecting respond rate of questionnaire that is shared. A/B testing is undertaken to facilitating this. Where a hypothesis is tested and bring a result. You can also found some exploratory data analysis here including seeing trends that happened

banking-deposit-target-prediction

Build model to predict whether a customer will subscribe to term deposit or not

car-auction-prices-project

The dataset contains historical car auction sales prices, scraped from the outside internet sources collected in 2015. This dataset taken from kaggle

data-analaysis-for-b2b-retail-customer

data-analysis-with-e-commerce-challenge

data-exploration-ford-gobike-project

Ford GoBike System Dataset includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area in the year 2017

demand-forecasting

Predicting the Sales using Time-series forecasting for month-wise data.

demand-forecasting-public-bike-rental-project

Developed multiple predictive models with 90% accuracy for forecasting the daily-hourly bike rental count using Python & Machine Learning techniques like Regression, Clustering, Ensemble, Neural Network to achieve maximum accuracy

eda-case-study-on-bank-loan

employee-turnover-project

Can you help reduce employee turnover?

exploratory-data-analysis-supermarket-sales

This is a practical project for data in three branches supermarket. There are several analysis and insights findings to have a better comprehension of the sales situation in the three branches, including total sales for each, the proportion of products line sold in each branch etc. There is also a correlation determination process between target data which in this case is the total sales to other data including both numerical and categorical data. The result of the correlation is useful as known to further analysis like the predictive analysis.

global-plastics-pollution

Top ten countries with the greatest change in plastic pollution between 2020 and 2019

learn-idcamp-dicoding

learn-sql

This is a collection of projects related to SQL. I use MySQL to run the code in this project.

medical-insurance-cost-project

In this project, we will analyze individual medical insurance cost and variables that may affect it.

netflix

Data preparation netflix (simple and complex queries)

project-bike-sales-in-europe

project-ecommerce-shipping-clasification-modeling

Exploratory Data Analysis & Modeling to predict whether the shipping deliveries will be received late or on-time by the customers

project-k-means-from-scratch

In this code, I tried to implement K-Means without any libraries (except the prior libraries for plot and dataframe). The hyperparams I used are k and maximum iterations, so I didn't set the tolerance limit here.

project-online-retail-dataset

Explore Online retail dataset and create customer segmentation using RFM (Recency, Frequency, Monetary) analysis. This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers.

segmentation-for-customer-satisfaction-with-r

Customer satisfaction is essential to keeping your current customers and retaining new ones. Dissatisfied customers are a retention risk, and losing them will hurt your brand. so important for brands to succeed.

superstore-project

uji-regresi-linier

Uji Regresi Linier

wahyunh10

Config files for my GitHub profile.