Sushant Menon (sushantmenon1)

sushantmenon1

User data from Github https://github.com/sushantmenon1

Home Page:https://www.sushantmenon.com/

GitHub:@sushantmenon1

Sushant Menon's repositories

graphreader

Implementation of the GraphReader paper.

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Time-Series

Application for predicting the total number of Receipts for a given month of 2022

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Face-Generation-using-Generative-Adversarial-Models

This project presents an innovative approach to generate anime faces using Generative Adversarial Networks (GANs). Leveraging the power of TensorFlow and Keras, we implemented a Generative Adversarial Network (DCGAN and WGAN) architecture to generate high-quality and novel anime faces from random noise inputs.

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Depression-Detection-from-Social-Networks

The "Depression Detection from Social Networks" project uses NLP and ML techniques to detect depression in individuals based on Twitter data, achieving 80% precision. It empowers early intervention and leverages machine learning for improved accuracy.

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diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

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Fine-Tuned-Stable-Diffusion

This repository is part of a task from Vermillo

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Machine-Learning-Notebooks

Developed various ML models in my Undergrad. Applied NLP techniques, and optimized performance. Achieved high accuracy rates and explored diverse datasets. Used libraries like nltk, pandas, numpy, scipy, seaborn, sklearn. Deep learning integration enhanced precision.

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Machine-Translation-Enabled-Sentiment-Analysis-Across-Multiple-Languages

Machine Translation-Enabled Sentiment Analysis Across Multiple Languages is a project that leverages data collection, language translation, and sentiment analysis techniques to analyze and classify sentiments in customer reviews across various languages, providing valuable insights into the opinions and feelings expressed by users.

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Retrieval-Augmented-Generation-Chatbot

Retrieval Augmented Generation App combines Google Flan T5, Pinecone DB, FastApi, Streamlit. Stores user embeddings for swift data retrieval, delivering a seamless and interactive experience.

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stock-app

Deployment

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Unity-ML-Agents-Training-a-Robot

Train a virtual robot to walk towards a target using Unity, ML Agents, and Reinforcement Learning. This project combines RL and Imitation Learning techniques to optimize the robot's movements. Explore the intersection of Unity, ML Agents, and RL, and learn to train intelligent agents for robotics and autonomous systems.

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VerboFad-Web-Application

VerboFad is a powerful web application utilizing the Transformer (T5) model to summarize, paraphrase, and analyze similarity scores between texts. With an intuitive interface and seamless navigation, it enhances productivity and efficiency for users.

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