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bankapp

bayesian-regression-to-predict-bitcoin-price-variations

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

bfs-and-dfs

Implementing BFS and DFS for a given graph

burger-builder

causal-discovery-between-manufacturer-retailer-price-channels

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.

computervision

expertiza

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.

gradience

CSC 540 Database Management System

graph-embeddings-for-recommender-systems

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.

internet-protocol

market-segmentation-using-attributed-graph-community-detection

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).

matching-algorithms-for-the-adwords-problem

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

music-recommender-system-

A music recommender system that will recommend new musical artists to a user based on their listening history.

pluralsight-course-using-react-hooks

Pluralsight Course Coming on React Hooks.. See this description and @pkellner for the announcement

skills-hello-github-actions

My clone repository

spot-it

supervised-learning-techniques-for-sentiment-analytics

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.

theeni-pandora

tic-tac-toe

Developed a Tic-Tac-Toe game using React.

twitter-sentiment-analytics-using-apache-spark-streaming-apis-and-python

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.

x.0

A web based intellectual vocabulary game application