sushmithashridhar
PSU🐿____________________________________ /\︿/\ ______________________________ \0 _ 0 /╱\╱ _______________________ \_︹_/
Portland,Oregon
Pinned Repositories
Neural-network-MNIST-dataset
The MNIST database is a large database of handwritten digits that is commonly used for training various image processing systems. The database is also widely used for training and testing in the field of machine learning. Goal is to predict the handwritten digits by implementing a two-layer neural network (i.e, one hidden-layer) to perform the handwritten digit recognition
Perceptron
Used a perceptron with 785 inputs (which includes the bias input) and 10 outputs to learn to classify the handwritten digits in the MNIST dataset (http://yann.lecun.com/exdb/mnist/). Performing training on the perceptrons with three different learning rates: η = 0.001, 0.01, and 0.1.
Python-Flask-web-application
Created a toy Python Flask web application for viewing anonymous reviews of courses. Application follows an MVP pattern and support two routes/views initially
Internetworking-Protocols-CS-594
IRC or Internet Relay Chat is an application that lets multiple users communicate via text messages with each other in common "virtual" rooms. Implements the functionality of being able to create a room, join a room, leave a room, and list rooms available. Other features such as private chat has been implemented.
Naive-Bayes-Classifier
Used Gaussian Naïve Bayes and Logistic Regression to classify the Spambase data from the UCI ML repository, which can be found here: https://archive.ics.uci.edu/ml/datasets/spambase
Coursera-Neural-Networks-and-Deep-Learning-
● Understand the major technology trends driving Deep Learning ●Be able to build, train and apply fully connected deep neural networks ●Know how to implement efficient (vectorized) neural networks ● Understand the key parameters in a neural network's architecture
awesome-interview-questions
:octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:
Breakout_Deterministic-v0
Gym library to simulate reinforcement learning environment, Atari game (BreakoutDeterministic). Play the BreakoutDeterministic-v4 environment using random actions
Buffer-manager
Implement a version of the Buffer Manager layer of Minibase, without support for concurrency control or recovery.
DQN-DDQN-on-Space-Invaders
Implementation of Double Deep Q Networks and Dueling Q Networks using Keras on Space Invaders using OpenAI Gym. Code can be easily generalized to other Atari games.
sushmithashridhar's Repositories
sushmithashridhar/awesome-interview-questions
:octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:
sushmithashridhar/Breakout_Deterministic-v0
Gym library to simulate reinforcement learning environment, Atari game (BreakoutDeterministic). Play the BreakoutDeterministic-v4 environment using random actions
sushmithashridhar/Buffer-manager
Implement a version of the Buffer Manager layer of Minibase, without support for concurrency control or recovery.
sushmithashridhar/Coursera-Neural-Networks-and-Deep-Learning-
● Understand the major technology trends driving Deep Learning ●Be able to build, train and apply fully connected deep neural networks ●Know how to implement efficient (vectorized) neural networks ● Understand the key parameters in a neural network's architecture
sushmithashridhar/DQN-DDQN-on-Space-Invaders
Implementation of Double Deep Q Networks and Dueling Q Networks using Keras on Space Invaders using OpenAI Gym. Code can be easily generalized to other Atari games.
sushmithashridhar/Final-db-project-CS-586
Implement a database, along with populating it with real data and producing example queries to execute over it.
sushmithashridhar/Internetworking-Protocols-CS-594
IRC or Internet Relay Chat is an application that lets multiple users communicate via text messages with each other in common "virtual" rooms. Implements the functionality of being able to create a room, join a room, leave a room, and list rooms available. Other features such as private chat has been implemented.
sushmithashridhar/ios-App
sushmithashridhar/Naive-Bayes-Classifier
Used Gaussian Naïve Bayes and Logistic Regression to classify the Spambase data from the UCI ML repository, which can be found here: https://archive.ics.uci.edu/ml/datasets/spambase
sushmithashridhar/Neural-network-MNIST-dataset
The MNIST database is a large database of handwritten digits that is commonly used for training various image processing systems. The database is also widely used for training and testing in the field of machine learning. Goal is to predict the handwritten digits by implementing a two-layer neural network (i.e, one hidden-layer) to perform the handwritten digit recognition
sushmithashridhar/Operating-Systems-CS-510
sushmithashridhar/OS_Tickless_Performance
sushmithashridhar/Perceptron
Used a perceptron with 785 inputs (which includes the bias input) and 10 outputs to learn to classify the handwritten digits in the MNIST dataset (http://yann.lecun.com/exdb/mnist/). Performing training on the perceptrons with three different learning rates: η = 0.001, 0.01, and 0.1.
sushmithashridhar/Python-Flask-web-application
Created a toy Python Flask web application for viewing anonymous reviews of courses. Application follows an MVP pattern and support two routes/views initially
sushmithashridhar/Space_Invaders