nakatuddesuzan

desktop-calculator

E-news-Project

An online news portal aims to expand its business by acquiring new subscribers. Every visitor to the website takes certain actions based on their interest. The company plans to analyze these interests and wants to determine whether a new feature will be effective or not. Companies often analyze users' responses to two variants of a product to decide which of the two variants is more effective. This experimental technique is known as a/b testing that is used to determine whether a new feature attracts users based on a chosen metric. Suppose you are hired as a Data Scientist in E-news Express. The design team of the company has created a new landing page. You have been assigned the task to decide whether the new landing page is more effective to gather new subscribers. Suppose you randomly selected 100 users and divided them equally into two groups. The old landing page is served to the first group (control group) and the new landing page is served to the second group (treatment group). Various data about the customers in both groups are collected in 'abtest.csv'. Perform the statistical analysis to answer the following questions using the collected data.

Flask-Docker-Nginx-uWSGI

Full-Stack-Django-React

mrm_api

React-ReactRouter-Flux

react-redux

nakatuddesuzan/E-news-Project

An online news portal aims to expand its business by acquiring new subscribers. Every visitor to the website takes certain actions based on their interest. The company plans to analyze these interests and wants to determine whether a new feature will be effective or not. Companies often analyze users' responses to two variants of a product to decide which of the two variants is more effective. This experimental technique is known as a/b testing that is used to determine whether a new feature attracts users based on a chosen metric. Suppose you are hired as a Data Scientist in E-news Express. The design team of the company has created a new landing page. You have been assigned the task to decide whether the new landing page is more effective to gather new subscribers. Suppose you randomly selected 100 users and divided them equally into two groups. The old landing page is served to the first group (control group) and the new landing page is served to the second group (treatment group). Various data about the customers in both groups are collected in 'abtest.csv'. Perform the statistical analysis to answer the following questions using the collected data.

nakatuddesuzan/Flask-Docker-Nginx-uWSGI

nakatuddesuzan/desktop-calculator

nakatuddesuzan/Full-Stack-Django-React

nakatuddesuzan/mrm_api

nakatuddesuzan/React-ReactRouter-Flux

nakatuddesuzan/react-redux

nakatuddesuzan/ah-backend-odin

nakatuddesuzan/download-web-image

nakatuddesuzan/EasyVisa

Machine Learning model to facilitate the process of visa approvals

nakatuddesuzan/Foodhub-Project

This project required analysis of data to give recommendations to the food hub business

nakatuddesuzan/IAHTerminal

nakatuddesuzan/INNS-Hotels-Project

A predictive model that can predict which hotel booking is going to be canceled in advance, and help in formulating profitable policies for cancellations and refunds.

nakatuddesuzan/Learning-Nodejs

nakatuddesuzan/level-up

nakatuddesuzan/Naive-Bayes-Classifier

Bayes' Theorem, Naive Bayes Classifier, Gaussian Naive Bayes

nakatuddesuzan/Netflix-Movies-Recommender

This recommender system is designed on the approach of content-based filtering. The content based filtering method for this project is based on the actors, directors, titles and genres of the movies.

nakatuddesuzan/Nth-Highest-salary-Leetcode

nakatuddesuzan/pymongo-flask-app

nakatuddesuzan/PySpark-Application

PySpark, Mlib, Apache Spark, Spark SQL

nakatuddesuzan/rebound

Command-line tool that instantly fetches Stack Overflow results when an exception is thrown

nakatuddesuzan/Recell

Uses Machine Learning(Linear Regression)

nakatuddesuzan/serving-react-with-flask

nakatuddesuzan/simple-react-app

nakatuddesuzan/simple-react-native-app

nakatuddesuzan/StackOverflow-lite

nakatuddesuzan/stackoverflowlite-db

nakatuddesuzan/Trade-and-Head

Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group. Skills and Tools EDA, Kmeans Clustering, Hierarchical Clustering, Cluster Profiling

nakatuddesuzan/USCC-Front-End

nakatuddesuzan/using-scrapy