Amogha A H (Amogha027)

Amogha027

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Location:Hyderabad

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Amogha A H's repositories

Airport-Management-DB

A fully-functional CLI-based database management system built using Python and MySQL.

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BackPropagation-algorithm

Implementation of Back Propagation algorithm along with its variants such as RProp and QuickProp.

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Car-Racing-Game

A 3D car racing game built using ThreeJS and WebGL

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Clash-of-Clans

Extended the code base of a terminal game in Python.

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Clinical-analytics-model

Created an analytical model for health of a cohort based on latest data using Cube.dev

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Data2Vis

Pytorch implementation of the paper Data2Vis using Encoder-Decoder architecture with attention mechanism.

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DCGAN-and-Diffusion-model

Implemented Deep Convolutional GAN and Diffusion Model architecture using Pytorch and compared the results of these models on CIFAR-10 dataset using the inception score.

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DSA-assignments

All the assignments of the course - Data Structures and Algorithms.

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DSA-codes

Standard Implementation of the data structures and algorithms.

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Enhanced-xv6

Tweaked the existing xv6 by adding system calls, three other scheduling policies, namely FCFS, PBS, MLFQ, and copy on write fork.

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Greddit

A online social media application built using MERN stack.

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Jetpack-Joyride

A 2D game similar to Jetpack Joyride built in C++ using OpenGL

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Ensemble-Learning

Implementation of two major ensemble learning methodologies, Bagging and Stacking, over the tasks of classification and regression. Also, compared the results of Random Forests with multiple Boosting Techniques.

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KDE-and-HMM

Implementation kernel density estimation (KDE) from scratch and used it to solve the bounding box problem. Also, applied hidden markov models (HMM) in the given two problems.

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Linear-Regression

Implemented bias-variance trade-off and linear regression in Jupyter notebook

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Linux-Shell

A user-defined Unix-based interactive shell program in C which supports all the shell commands

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PCA-and-Clustering

Implemented the Principal Component Analysis (PCA) & performed dimensionality reduction. Implemented Hierarchical clustering EM algorithm for GMM and performed the clustering operations.

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Perceptron-algorithm-and-CNN

Implementation of perceptron algorithm for both classification and regression tasks. Trained a CNN model on the MNIST dataset and also implemented the autoencoder to denoise the noisy MNIST dataset.

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RNN-LSTM

Implementation of RNN (Recurrent Neural Network) for Auto Regressive Models and learning the long term dependencies using LSTM (Long short-term Memory).

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Safety-Device-for-Fall-Detection

A safety device which detects the fall of industrial worker from chimneys

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Smart-Home-Security-Device

A smart IoT device which detects human movement in its environment

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Supervised-ML-Algorithms

Implemented separate classes for the supervised machine learning algorithms, k Nearest Neighbours algorithm and Decision Tree algorithm.

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Transformers

Pytorch implementation of Transformers model from scratch. Also, implemented Denoising Autoencoder to remove noise from an MNIST image.

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