InnovateTheExisting's starred repositories
StackExchange.Redis
General purpose redis client
Azure-in-bullet-points
☁️ Azure summary in bullet points
Community-Policy
This repo is for Microsoft Azure customers and Microsoft teams to collaborate in making custom policies.
Real-Time-Streaming-Data-Pipeline-and-Dashboard
Building Real Time Data Pipeline using Apache Kafka, Apache Spark, Hadoop, PostgreSQL, Django and Flexomonster on Docker to track status of Servers in the Data Center across the Globe.
Cyber-Attack-Attribution-with-Machine-Learning
Cyber attack attribution is the process of attempting to trace back a piece of code or malware to a perpetrator of a cyberattack. As cyber attacks have become more prevalent, cyber attack attribution becomes more valuable. The process of cyber attack attribution can be done using reverse engineering. From the metadata of the malware executable file, we can gather data such as date of creation, variable names used, and what library calls are imported. This information can be used as features for attribution analysis. We need to extract the features from malware that can be used for attribution and analyse them using some technique to attribute the attacks.
udacity-data-engineering-capstone
Capstone Project for Udacity Data Engineering Nanodegree
Brain-Tumor-Detection-with-Deep-Learning
In this project there was application of Deep Learning to detect brain tumors from MRI Scan images using Residual Network and Convoluted Neural Networks. This automatic detection of brain tumors can improve the speed and accuracy of detecting and localizing brain tumors based on MRI scans. This would drastically reduce the cost of cancer diagnosis and help in early detection of tumors without any human involvement and would essentially be a life saver. We have also compared the accuracy of results obtained by using two different models - ResNet50 and ResNet18 and used Transfer Learning to tune or freeze weights to evaluate what gives best result.There are 3929 brain MRI scans which are either positive or negative cases of brain tumor. Models were built using ResNet50 and ResNet18 and evaluated their performance in detecting positive or negative cases of brain tumors.
Software-Engineering-Virtual-Experience-insidesherpa
JPMorgan organised a software virtual experience through the InsideSherpa. Over the period of April 2020 to May 2020, I have completed practical task modules in: 1.Establishing Financial Data Feeds 2.Frontend Web Development 3.Data Visualization with Perspective
Big-Data-Management-Analytics-Project
Final Project for CS 6350.001 - Large Scale Data Collection and preprocessing in Spark
JPMorgan_Virtual_Internship_2020
This repository contains various tasks given by JPMorgan Chase & Co. Software Engineering Virtual Internship, the pathch files and my certificate of completion.
Data-Engineer-Nanodegree
This repository contains projects from udacity Data Engineer Nanodegree program
JP-Morgan-Virtual-Internship
This Repository Contains all my Work done during JP Morgan Virtual Internship Experience.
Bigdata-Management-and-Analytics
CS 6350 Big Data Analytics and Management (Graduate Level) Spring 2020
Big_Data_Assignments
Usage of Apache Hadoop, Spark and Kafka.
CS6360_Project
CS6360_Project
InsideSherpa
JPMorgan Chase & co.
Software-Engineering-VirtualExperience
JPMorgan Chase & Co. | InsideSherpa
JPMC-insidesherpa
This repository contains the submitted patch files.Virtual Engineering Experience By JP Morgan Chase & Co.
CS6350-Big-Data-Management-and-Analytics
Course project for Big Data Management and Analytics taught by Anurag Nagar at UT Dallas.