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Gautham Pughazhendhi's Projects

ann-chatbot icon ann-chatbot

A simple retrieval model-based chatbot implemented using a feed-forward artificial neural network.

broadcaster icon broadcaster

A simple Java-based socket program for broadcasting messages to the listening clients using multi-threading.

digit-recognizer icon digit-recognizer

A simple jupyter notebook to classify hand-written digit images using K-nearest neighbor algorithm and artificial data synthesis.

earthosys-tsunami-alert-system icon earthosys-tsunami-alert-system

Earthosys is a project to predict the occurrence of tsunamis using Machine Learning and create tsunami alerts using IoT and cloud.

forest-fire-area-prediction icon forest-fire-area-prediction

This project aims to predict the burned area of forest fires in the northeast region of Portugal, using meteorological and soil moisture data.

handson-ml2 icon handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hangar-py icon hangar-py

Hangar is version control for tensor data. Commit, branch, merge, revert, and collaborate in the data-defined software era.

ifind icon ifind

A simple iOS application that uses Yelp API to load the restaurants near the user's location.

ihub icon ihub

A simple iOS application that keeps track of your github followers.

llama2.py icon llama2.py

Inference Llama 2 in one file of pure Python

matplotlib-starter icon matplotlib-starter

A simple jupyter notebook to create different types of basic plots using matplotlib python library and Canadian immigration dataset.

mnist-prediction icon mnist-prediction

A simple module to predict the handwritten digits in the MNIST dataset using feed-forward and recurrent neural networks.

pycounts_gp icon pycounts_gp

A practice repo to create a simple python package to count words in a text file using cookiecutter.

react-apps icon react-apps

Collection of React applications with UX, mock JSON data, and assets. The collection illustrates both basic, and advanced concepts in React.

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