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Welcome to the Pytorch Essentials repository! This Repo aims to cover fundamental to advanced topics related to PyTorch, providing comprehensive resources for learning and mastering this powerful deep learning framework.
MuskanAi is a personal Digital Assistant which is capable of performing all Automation task whether it is Controlling your Devices, Browsing the Internet and Emotional Understanding..
This repository contains the implementation of a Transformer-based model for abstractive text summarization and a rule-based approach for extractive text summarization.
Explore our "LLM Tutorials" GitHub repository for comprehensive guides on using large language models (LLMs) like Llama 2 with PyTorch. Discover practical examples, code snippets, and expert insights to enhance your NLP projects with the latest techniques in language modeling.
Analysis of Hotel Booking Cancellation dataset using statistical model and provide predictions on future booking cancelations using Logistic regression model.
Text Processing RNN leverages RNN and LSTM models for advanced text processing. It features deep learning techniques for NLP tasks, utilizing GloVe for word embeddings, aimed at both educational and practical applications.
Education purpose project to create a recomendation posts service for random social network / Учебный проект по созданию рекомендательной системы постов в рамках программы Karpov.Courses Start ML.
RiverText is a framework that standardizes the Incremental Word Embeddings proposed in the state-of-art. Please feel welcome to open an issue in case you have any questions or a pull request if you want to contribute to the project!
Built an NLP pipeline and integrated a neural network model using PyTorch. Utilises Relu activation function with 3 linear layers. Intent is to build on this project to create dynamic NPC's in games.
The aim of this repository is to show a baseline model for text classification by implementing a LSTM-based model coded in PyTorch. In order to provide a better understanding of the model, it will be used a Tweets dataset provided by Kaggle.