aarivan Goto Github PK
Name: Abhilash Arivanan
Type: User
Location: Seattle, WA
Name: Abhilash Arivanan
Type: User
Location: Seattle, WA
predicting the price variations of bitcoin, a virtual cryptographic currency. These predictions could be used as the foundation of a bitcoin trading strategy. To make these predictions, you will have to familiarize yourself with a machine learning technique, Bayesian Regression, and implement this technique in Python
Implementing BFS and DFS for a given graph
Overview Identifying the strategy employed by business firms has motivated empirical research towards studying a firm’s behavior. If there exists a specific pattern that can describe the interactions between the manufacturers and retailers, the application of causality analysis on their pricing interaction can clarify their strategic behavior. The interactions between the manufacturer and retailer can be discussed to follow a verticalintegrated system or Stackelberg leadership bilateral-monopoly model. In a vertical-integrated system, the manufacturer and retailer cooperate to maximize the profit of the distribution channel instead of individual profit. The important character of this model is that both the manufacturer and retailer affect the sales of the product.
Expertiza is a web application where students can submit and peer-review learning objects (articles, code, web sites, etc). The Expertiza project is supported by the National Science Foundation.
CSC 540 Database Management System
In this project, we will revisit the problem central to recommender systems: predicting a user’s preference for some item they have not yet rated. Like the Spark recommender from the first project, we will use a collaborative filtering model to explore this problem. Recall that in this model, the goal is to find the sentiment of a user about a particular item Unlike the the first project that used the ALS method, however, we will perform this task using a graphbased technique called DeepWalk.
Overview: Market segmentation divides a broad target market into subsets of consumers or businesses that have or are perceived to have common needs, interests, and priorities. These segments help firms or businesses focus on their target groups effectively and allocate resources efficiently. Traditional segmentation methods are solely based on attribute data such as demographics (age, sex, ethnicity, education, etc.) and psychographic profiles (lifestyle, personality, motives, etc.). However, social networks have recently become important for marketing. Depending on the nature of the market, social relations can even become vital in forming segments. Such social relations combined with demographic properties can be used to find more relevant subsets of consumers or businesses (i.e., communities).
Problem: We are given a set of advertisers each of whom have a daily budget Bi . When a user performs a query, an ad request is placed online and a group of advertisers can then bid for that advertisement slot. The bid of advertiser i for ad request q is denoted as bi q. We assume that the bids are small with respect to the daily budgets of the advertisers (i.e, for each i and q, b iq << Bi ) . Moreover, each advertisement slot can be allocated to at most one advertiser and the advertiser is charged his bid from his budget. The objective is to maximize the amount of money received from the advertisers
A music recommender system that will recommend new musical artists to a user based on their listening history.
Pluralsight Course Coming on React Hooks.. See this description and @pkellner for the announcement
My clone repository
Perform sentiment analysis over IMDB movie reviews and Twitter data. Our goal will be to classify tweets or movie reviews as either positive or negative.
Developed a Tic-Tac-Toe game using React.
About processing live data streams using Spark’s streaming APIs and Python. We will be performing a basic sentiment analysis of real-time tweets. In addition, a basic introduction to Apache Kafka.
A web based intellectual vocabulary game application
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.