Shreenidhi N's repositories
Reinforcement-Learning-based-Movie-Recommendation
Recommender Systems are the systems designed to that are designed to recommend things to the user based on many different factors. These systems predict the most likely product that the users are most likely to purchase and are of interest to. Recommendations typically speed up searches and make it easier for users to access content they’re interested in, and surprise them with offers they would have never searched for. In this project work, we explore the use of Reinforcement Learning based techniques to solve the problem of Movie Recommendation. We have implemented the following strategies: Multi Armed Bandits based recommender and an Actor-Critic based recommender framework using Deep Reinforcement Learning.
Image-Compression-using-DCAE
Deep Convolutional AutoEncoder-based Lossy Image Compression
BitCoin-Price
BitCoin Price, developed using Python using data from Yahoo Finance. The white noise in the data checked using the Ljung Box test. Finding standard deviation, moving average and bollinger bands as parameters of the closing prices, to classify whether it goes up or down, using Logistic regression, Support vector classifier and random forest. The price prediction models using an ARIMA time series model.
Fooderia
Our project , ‘ Fooderia’ aims to simulate the working of a database centric web application to order food. A connection between the database and the User Interface is done and the User Interface interacts with the database efficiently, by means of Stored Procedures and Functions.
-Concurrency-of-Database-in-C
Concurrency of Database,developed using POSIX library in C, to design and implement a concurrent access library operating on a warehouse database. The concurrent library receives requests from client threads and forwards this request onto the products database interface that allows users tocreate, update,modify,delete and other access operations on product details of the database. The POSIX library functions were used to achieve synchronization without losing the consistency of data and act as a wrapper of the database interface.
Customer-Segmentation
Customer Segmentation Analysis, developed using Python, by using Clustering Algorithm for the purpose of dividing the customers into groups based on the similarity in different ways that are relevant to marketing such as location, items, spending score, salary and accordingly identify customers’ behavior and interests and focus on them for future benefits of the company.
KNN-Algorithm-from-Scratch
Implementing K Nearest Neighbours Algorithm on Wisconsin Breast Cancer Dataset(WBCD) without using built in function for KNN algorithm. The data is split into 3 : train, validation and test data. The performance metrics are calculated for different K values.
Simple-Proxy-server-and-DOS-attack-
The Project aims to create a Proxy Server - Client program which implements the Cache memory using the Linked List Data Structure along with a Denial-of-Service attack on the server . The project is implemented using Python and socket programming.
AdConversions-Web-Analytics-
Advertisement Conversions Dataset is taken from kaggle. The dataset consists of an anonymous organisation’s social media ad campaign details and other details recorded.
AWS-KMS-demo
AWS Key Management Service (KMS) is a managed service that makes it easy for you to create and manage keys and control the use of encryption across a wide range of AWS services.
Eigenfaces-FacialRecognition
Eigenfaces, using Linear Algebra to implement Facial Recognition application.
Census-Data-Analysis-in-Python-
The US Census Analysis(2015), developed using Python, for the purpose of analyzing various demographic and economic factors affecting the state of affairs in different Counties in the US.Multiple types of graphs were visualized using ‘matplotlib’ library and the user interface was created using ‘tkinter’ module.
CYK-Parsers
A simple CYK Recognizer and Parser implemented from scratch in Python . The module implements the conversion of CFG to CNF and parsing using the CNF . An extended version of CFG , Probabilistic CFG is included to find the most probable parse tree for a given sentence using Probabilistic CYK Algorithm.
Fuzzy-String-Search
Fuzzy String Search, developed using C++, to implement fuzzy string matching. This is done using the Data Structure, BK-Trees. Given a file containing words, the contents are extracted and inserted to the BK-Tree to enable searching and spelling corrections.
Gadget-shop-Technostatico-in-C-
Using Data Structures : Multiple Linked Lists
Logistic-Regression-Sample-in-R
A small example of Logistic Regression in R for a data set.
Monopoly-2-player-game-C
Mini Monopoly, developed using C, which is a two-players board game. The rectangular board with multiple squares having countries and their costs, colours blue and red representing the two players was implemented using ‘graphics.h’ header file.Dice rolled by players are randomly generated. Bonus points and fines are collected based on place of landing. The winner has greater points at the end of the game.
ShoppingStore-Files-OOP
Shopping Mall management project using C++. Focus on File read, write, modify.
Social-Networks-Community-Fuzzy
Fuzzy-rough community in social networks