I'm a data analyst based in California.
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Name: Deandra
Type: User
Twitter: data_deandra
Location: California
I'm a data analyst based in California.
Answers to 120 commonly asked data science interview questions.
In this project, I cleaned, analyzed, and plotted employee exit survey data to find out whether employees are resigning due to job dissatisfaction, and whether younger employees are more dissatisfied than older employees.
I analyze Billboard number-one singles from each decade (1950s - present) to generate insights about how music has changed over time, and if songs that go number-one have similar attributes.
exploratory data analysis based on survey results
:bathtub: Clean Code concepts adapted for machine learning and data science
A Code-First Introduction to NLP course
if you truly want to know whether NYC is better than San Francisco
working through Cracking the Coding Interview 6th Edition, in Python
create SQL database for MLB data
Discoverify uses signal processing and audio features from the Spotify-API to recommend songs. An offshoot of my Friendshipify app.
AKA Friendshipify. This is the repository for my multi-user music recommender that analyzes the music taste of two people, finds the similarities between their taste, and generates a playlist of songs based on that similarity.
I compare which types of HackerNews posts are more popular
Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python
I use logistic regression and random forests to build a model that can predict whether or not a borrower will pay off their loan
I experiment with linear regression and random forests to build a model that can predict, using NLP methods, the number of upvotes a HackerNews article will receive based on the headline.
A refactoring of my old Coursera project; I wanted to answer, based on neighborhood venue types, whether Manhattan or San Francisco offers more "bang for your buck." I compared rent prices and venues per neighborhood for both cities. I used k-means clustering analysis and leveraged data using the Foursquare API.
I explore using the K Nearest Neighbors algorithm with AirBnB data
This is my portfolio of data science projects. Descriptions of each project can be found in the README as well as links to their repositories and notebook viewer.
I used decision trees and random forests to build a model that predicts the number of bike rentals on a given day
answer business questions using SQL
Repo of notebooks where I followed tensorflow tutorials.
answer questions about job outcomes of college graduates
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.