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pravin reddy's Projects

conv_s2s icon conv_s2s

Convolutional Sequence-to-Sequence (Work in Progress)

coolbuttons icon coolbuttons

Cool, glassy iOS buttons with only one color to set.

corebluetooth-demo icon corebluetooth-demo

New iOS5 framework to connect with Low-Energy devices. Actually this framework cannot connect with "traditional" bluetooth devices, iPhone4S will have a "switcher" that will allow to connect LE-devices and "tradicional" bluetooth devices.

corenlp icon corenlp

Stanford CoreNLP: A Java suite of core NLP tools.

coreparse icon coreparse

A shift/reduce parsing framework for Mac OS X and iOS

countmemaybe icon countmemaybe

A set of distinct value estimators that give probabilistic bounds on a sets cardinality

coursera-dl icon coursera-dl

Script for downloading Coursera.org videos and naming them.

courses icon courses

Course materials for escience curricula

courses-1 icon courses-1

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

cowboy icon cowboy

Small, fast, modular HTTP server written in Erlang.

cppn-gan-vae-tensorflow icon cppn-gan-vae-tensorflow

Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.

cryptocoding icon cryptocoding

CryptoCoding is a superset of the NSCoding protocol that allows for simple, seamless AES encryption of any NSCoding-compatible object.

cryptose icon cryptose

Cryptose is a cryptogram game for iOS and Android with three gritty occupations to choose from. Made with Marmelade SDK.

cs221-car icon cs221-car

This assignment is a modified version of the Driverless Car assignment written by Chris Piech. A study by the World Health Organisation found that road accidents kill a shocking 1.24 million people a year worldwide. In response, there has been great interest in developing autonomous driving technology that can can drive with calculated precision and reduce this death toll. Building an autonomous driving system is an incredibly complex endeavor. In this assignment, you will focus on the sensing system, which allows us to track other cars based on noisy sensor readings. Getting started. Let's start by trying to drive manually: python drive.py -l lombard -i none You can steer by either using the arrow keys or 'w', 'a', and 'd'. The up key and 'w' accelerates your car forward, the left key and 'a' turns the steering wheel to the left, and the right key and 'd' turns the steering wheel to the right. Note that you cannot reverse the car or turn in place. Quit by pressing 'q'. Your goal is to drive from the start to finish (the green box) without getting in an accident. How well can you do on crooked Lombard street without knowing the location of other cars? Don't worry if you aren't very good; the staff was only able to get to the finish line 4/10 times. This 60% accident rate is pretty abysmal, which is why we're going to build an AI to do this.

customermanager icon customermanager

CustomerManager AngularJS/BreezeJS Application with a custom route provider.

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