Hi, I'm Srikanth, a BTech student at Jain University, Bangalore, specializing in Cloud Technology and Mobile Applications. I pride myself on being responsible and organized, and I'm eager to embark on my professional journey. I'm looking forward to securing a role where I can fully utilize my training and skills, contributing to the success of a forward-thinking company.

HEALTH PREDICT APPLICATION

I developed a Health predict Application by using the technology Java Language with the help of Android Studio Enrolment. This Application is nothing but the user input values like(Hemoglobin, milk intake, diabetes data, meal intake etc..)with respective to their Health, the application processes the input values and predict the future diseases of user. I used some algorithms in this project called ANN (Artificial Neural Network) by using this algorithm predict the diseases

Calculator

The Calculation Application is an easy application for performing the basic and advanced mathematical calculations effectively. It performs operations such as addition, subtraction, multiplication, and division. This app has a clean, responsive UI for the ease of inputting and results. Built using Android Studio and Java/Kotlin, it ensures accurate computation and smooth performance on all Android devices.

Portfolio

I designed and deployed my personal portfolio using programming languages HTML and CSS, that includes Box Model and Flex box concepts and deployed it online through GitHub. Technology Used: HTML, CSS, JAVA SCRIPT. Tools Used: Visual Studio Code, GitHub.

Malicious Insiders

I'm currently working on this project, this project is to detect the malicious insiders who stole or sell the sensitive data within an organization or outside the world

Resource allocation in cloud computing using Reinforcement Learning (RL)

In cloud computing, resource allocation is a crucial process that aims to maximize the utilization of computational resources to effectively meet a range of needs. Conventional approaches frequently find it difficult to adjust to the complex and dynamic nature of cloud systems. A promising approach is provided by the machine learning subfield of reinforcement learning (RL), which allows systems to interact with the environment to learn the best resource allocation strategies.