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100days100projects

Creating 100 Projects in 100 Days Challenge

2013-pycon-awesome-big-data-algorithms

2020-05-react-advanced

2020-06-react-advanced

2021-new-grad

247-p2

Part 2 cs247 project

6.036

Homework solutions of Intro to ML course at MIT Spring 2018

aa-prep-work

acm-icpc

Solutions to some of my solved programming problems of icpc, codejam ...

acm-icpc-1

ad-papers

Papers on Computational Advertising

adhearsion

A Ruby framework for building telephony applications

advanced-algorithms

I have solved coding challenges in Codesignal/codefight in C++, Javascript, Java, Python

advent_of_code

ai-deadlines

:alarm_clock: AI conference deadline countdowns

ain

airbnb

airbnb-1

airbnb coding question

airbnb-2

Analyze AirBnB public data for San Francisco to answer the question 'What makes people choose your AirBnB home?'

airbnb-accessment

This is a question to test your AirBnB Server Knowledge using ruby.

airbnb-challenges

Answering some questions on AirBnB date from San Francisco

airbnb-data-collection

Data collection for Airbnb listings.

airbnb-interview-problem

AirBnB Interview

airbnb-new-york-data-analysis

Welcome to the Exploratory Analysis of the Airbnb Dataset! In this project, we aim to understand Airbnb rental landscape in New York City through exploratory analysis on the Airbnb dataset. Through static and interactive visualizations, we try to answer the below questions: How do prices of listings vary by location? How does the demand for Airbnb rentals fluctuate across the year and over years? Are the demand and prices of the rentals correlated? What are the different types of properties in NYC? Do they vary by neighborhood? What localities in NYC are rated highly by guests? What makes a host Super host? Do regular hosts and super hosts have different cancellation and booking policies? Are there any common themes that can be identified from the free-text section of the reviews? What aspects of the rental experience do people like and what aspects do they abhor? The data files that have been uploaded are compressed versions since they exceed Github's 100Mb limit. You'll need to extract these files before you run the code.

airbnb-prices

Airbnb Prices

airbnb-seattle-data-study

Studying the data from AirBnb to answer questions around price

airbnb-zillow-price_prediciton

The objective of this report is to find hidden insights from publicly available data of Airbnb and Zillow and further provide recommendations on which zip code have the highest return ratios within New York City and what are the most significant factors contributing to the revenue. Our goal is to help develop a data product and tailor client’s data strategies, whose part of its business model relies on short term rentals, to the market demand. Data visualization and predictive statistical models would be employed in the report to better answer our business questions.

airbnb_analysis

Project on Airbnb Price analysis which turn hard data into useful insights and compelling stories. Following questions can be answered based on this price analysis - What causes difference in Price listing ? Where to invest a property in San Fransisco? What is the seasonal pattern of rental prices? Visualizing sentiment analysis, customer satisfaction and different features.

airbnb_data_analyst

An analyst report for AirBnb dataset, this project aims to follow the CRISP-DM to address the three questions which related to business or real-world applications.

airbnb_interview

Airbnb interview question solve