Full Stack Engineer@DoorDash Canada | Previously at LinkedIn, Paytm

Rakesh Meena  • Peerlist

Discover more of what you love, snap and find products. A real-time Trending Feed, Stunning.  editorials and shopping guides. 
Expertise :- android layouts, JSON parsing,android database(SQLite and Realm ), third-party apis, cloudsight API for image search, Retrofit, ButterKnife, Proguard for shrinking code andresources to make APK size small, Firebase push notifications.

Hook E-commerce Mobile Application

A powerful and easy-to-use Android App, This App enables you buy HDFC-Life policy and calculate premiuminvestment amount for getting better retirement corpus amount .
Expertise :- android layouts, web-services integration in android app(REST and SOAP), JSONparsing, android database(SQLite and GreenDao ), android services, XML parsing, third-party apis, Retrofit, ButterKnife.

Life Insurance Mobile Application

The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for
reliable anti-spam filters. 
Machine learning techniques now days used to automatically filter the spam e-mail in a very successful rate.
In this project we build some of the most popular machine learning methods (Multinomial Bayesian classification, K-NN and SVMs) and compare their performance with respect to each other.
Tools Used: LIBSVM
Languages Used: Java, C++

Spam Email Classification

This project is aimed at adapting Parallel K-means algorithm based on map reduce framework 
using Hadoop to make the clustering method applicable to large scale data. 
We compared parallel k-means with serial k means. We use speedup, scaleup and sizeup to evaluate the performances of our proposed algorithm. 
The results show that the proposed algorithm can process large datasets on commodity hardware effectively.
Tools Used: Apache Hadoop version 1.2.1.

Parallel K-means Clustering

The Main aim of this project is to design Online shopping System which is used to provide a online interface to E- users (online users )  to buy and sell goods by sitting at home through internet. we designed back-end using java and used oracle 10g for data storage !!
Languages Used: Java.
Tools Used: Netbeans, Oracle10g.