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coding-interview-university

A complete computer science study plan to become a software engineer.

ctci-solutions

Python solutions to Cracking the Coding Interview (6th edition)

friend-recommender-in-social-network

genetic-algorithm-to-produce-user-define-string

Implementation of a Genetic Algorithm which aims to produce the user specified target string. This implementation calculates each candidate's fitness based on the alphabetical distance between the candidate and the target. A candidate is selected as a parent with probabilities proportional to the candidate's fitness. Reproduction is implemented as a single-point crossover between pairs of parents. Mutation is done by randomly assigning new characters with uniform probability.

genetic-programming-for-feature-selection-and-classification

ircode

This project discusses the efficiency and features of the popular Java Language-based search engine.Emphasis of this analysis is based on Lucene Index writing package of the search engine which includes token parsing,token scanning, indexing,searching, Highlighting. Alternatively, we attempt to perform stop word, page rank, clustering and its other features.

library

📚 Collection of various guides, books and papers.

multimodal-fakenews-detection

The proliferation of fake news on social media sites is a serious problem with documented negative impacts on individuals and organizations. A fake news item is usually created by manipulating photos, text, or videos that indicate the needformultimodaldetection.Researchersarebuildingdetection algorithms with an aim for high accuracy as this will have a massive impact on the prevailing social and political issues. A shortcoming of existing strategies for identifying fake news is their inability to learn a feature representation of multimodal (textual+visual) information. In this paper, we present a novel approach using a Cultural Algorithm with situational and normative knowledge to detect fake news using both text and images. An extensive set of experiments have been carried out on realworld multimedia datasets collected from Weibo and Twitter. The proposed method outperforms the state-of-the-art methods for identifying fake news in terms of accuracy by 9% on average.

network-instrustion-detector-using-anova-feature-selection

practice-python

Part of my daily plan for studying Python.

predicting-house-sales-in-king-county-usa

Project of Data Analysis with Python from Coursera

python-outlier-detection-pyod-

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

salaryprediction

video-recommender-system

Recommender systems are an important part of information and e-commerce ecosystem. They represent a powerful method for enabling users to filter through large information and product spaces. Nearly past years of research on collaborative filtering have led to a varied set of algorithms and a classic collection of tools and software for evaluating their performance. Research in the field is moving in the direction of a richer understanding of how recommender technology may be embedded in specific domains. The variety of personalities exhibited by different recommender algorithms show that recommendation is not a one-size-fits-all problem. Domain specific tasks, information needs, and item domains represent unique problems for recommenders, and design and evaluation of recommenders needs to be done based on the user tasks to be supported. Effective deployments must begin with proper analysis of prospective users and their goals. Based on this analysis, system developer has a host of options for the choice of algorithm and for its embedding in the user experience. This report describes what we did on the course project, including the details of how our video recommender system works and the techniques we used. The target of this project is to develop a video recommender system. The basic functions include recommendation of videos for particular user. Some other improvements are also provided, like testing and evaluation on different datasets. Also, the system is combined with some advanced algorithms, such as collaborative filtering, correlation coefficient, hold out test.