Pinned Repositories
Market-Segmentation
In this project, we will apply unsupervised learning techniques to identify segments of the population that form the core customer base for a mail-order sales company in Germany. These segments can then be used to direct marketing campaigns towards audiences that will have the highest expected rate of returns. The data that we will use has been provided by Bertelsmann Arvato Analytics, and represents a real-life data science task.
Conversion-Rate
The goal of this challenge is to build a model that predicts e-commerce conversion rate and, based on the model, come up with ideas to improve it.
Funnel-Analysis
The goal is to perform funnel analysis for an e-commerce website.
Customer-Identification
This project aims at identifying potential customers to target by predicting their income levels.
Adverstisement-of-company-website
The project analyses the Advertisement dataset of a company website to the probability of the internet user clicking on the advertisement
customer-database
This project addresses the issue an e-commerce firm is facing- should the firm focus on its mobile app or website ?
Image-Classifier
In this project, we'll train an image classifier to recognize different species of flowers. We can imagine using something like this in a phone app that tells us the name of the flower our camera is looking at. In practice we will train this classifier, then export it for use in our application.
autoEDA-resources
A list of software and papers related to automatic and fast Exploratory Data Analysis
Breast-Cancer-Detection
data-engineering-nanodegree
notebooks produced throughout the Udacity's Nanodegree Data Engineering Course
araj2's Repositories
araj2/system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
araj2/Starbucks-
araj2/shap
A game theoretic approach to explain the output of any machine learning model.
araj2/Restaurant-Analysis
This project conducts an NLP analysis of scraped YELP Review Data
araj2/Disaster-Response-Pipeline
araj2/python-geospatial
A collection of Python packages for geospatial analysis with binder-ready notebook examples
araj2/autoEDA-resources
A list of software and papers related to automatic and fast Exploratory Data Analysis
araj2/Funnel-Analysis
The goal is to perform funnel analysis for an e-commerce website.
araj2/Conversion-Rate
The goal of this challenge is to build a model that predicts e-commerce conversion rate and, based on the model, come up with ideas to improve it.
araj2/vowpal_wabbit
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
araj2/Image-Classifier
In this project, we'll train an image classifier to recognize different species of flowers. We can imagine using something like this in a phone app that tells us the name of the flower our camera is looking at. In practice we will train this classifier, then export it for use in our application.
araj2/Finding-Donors-for-CharityML
In this project, we will employ several supervised algorithms of our choice to accurately model individuals' income using data collected from the 1994 U.S. Census. We will then choose the best candidate algorithm from preliminary results and further optimize this algorithm to best model the data. Our goal with this implementation is to construct a model that accurately predicts whether an individual makes more than $50,000. This sort of task can arise in a non-profit setting, where organizations survive on donations. Understanding an individual's income can help a non-profit better understand how large of a donation to request, or whether or not they should reach out to begin with. While it can be difficult to determine an individual's general income bracket directly from public sources, we can (as we will see) infer this value from other publically available features.
araj2/start-here-guidelines
Guidelines on how this open source community works
araj2/data-engineering-nanodegree
notebooks produced throughout the Udacity's Nanodegree Data Engineering Course
araj2/Portfolio-Projects
araj2/Market-Segmentation
In this project, we will apply unsupervised learning techniques to identify segments of the population that form the core customer base for a mail-order sales company in Germany. These segments can then be used to direct marketing campaigns towards audiences that will have the highest expected rate of returns. The data that we will use has been provided by Bertelsmann Arvato Analytics, and represents a real-life data science task.
araj2/Customer-Identification
This project aims at identifying potential customers to target by predicting their income levels.
araj2/SQL-Advanced-Queries
SQL Practice Queries
araj2/Loan-Credit-Analysis
For this project we will be exploring publicly available data from LendingClub.com.
araj2/Breast-Cancer-Detection
araj2/Adverstisement-of-company-website
The project analyses the Advertisement dataset of a company website to the probability of the internet user clicking on the advertisement
araj2/customer-database
This project addresses the issue an e-commerce firm is facing- should the firm focus on its mobile app or website ?
araj2/StarbucksCapstoneChallenge
Udacity Data Scientist Nanodegree Project - Analyze Starbucks Capstone Challenge Dataset
araj2/notebooks
Speedml Python Notebooks