Building a text generation model from scratch
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Updated
May 15, 2024 - Jupyter Notebook
Building a text generation model from scratch
Repo for Implementing Research Papers & Projects related to Machine Learning
Deep convolutional and LSTM feature extraction approach with 784 features.
A bangla chatbot using bidirectional lstm
NLP-clustering(word) -Vietnamese Sentiment Analysis using artificial neural network
pytorch下基于transformer / LSTM模型的彩票预测
LSTM-ARIMA with Attention and Multiplicative Decomposition for Sophisticated Stock Forecasting.
This repo features a python implementation helps figuring out how lstm actually work
EQTransformer, a python package for earthquake signal detection and phase picking using AI.
Predicting popular cryptocurrency prices with LSTM and other analyses on stock and crypto prices
This research aims to develop a model for predicting the price of Bitcoin, Ethereum, Monero and Ripple using deep learning and evaluate its performance.
Generate Lyrics Using RNN.
machine learning introduction, featuring Python, TensorFlow, Keras, examples... and love
This project showcases a dataset of Amazon Reviews in Hindi, which we created ourselves. We applied various machine learning methods including Naive Bayes, SVM, and Decision Tree, using both Bag-of-Words and TF-IDF. Additionally, we experimented with deep learning techniques such as Feedforward Neural Networks and LSTM with ELMO embeddings.
Complete project of predicting the weather condition using Deep Learning
Welcome to the Lotto 6 aus 49 Prediction Project! This repository contains predictive models and analyses for Lotto 6 aus 49, a popular lottery game in Germany. Through statistical analysis, machine learning models, and simulations, we aim to provide insights and predictions to help lottery enthusiasts make informed decisions. BE AWARE! FUN PROJECT
The dataset used in this project consists of 50,000 IMDB movie reviews, evenly split into 25k reviews for training and 25k for testing. Each review is labeled as either positive or negative.
Projects and Models built in Python leveraging PyTorch, implementing Reinforcement Learning algorithms for reward-based tasks.
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