There are 0 repository under lstms topic.
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
Layer-wise Relevance Propagation (LRP) for LSTMs.
Predict Vehicle collision moments before it happens in Carla!. CNN and LSTM hybrid architecture is used to understand a series of images.
Implementation of the paper Recurrent Independent Mechanisms (https://arxiv.org/pdf/1909.10893.pdf)
The course is contained knowledge that are useful to work on deep learning as an engineer. Simple neural networks & training, CNN, Autoencoders and feature extraction, Transfer learning, RNN, LSTM, NLP, Data augmentation, GANs, Hyperparameter tuning, Model deployment and serving are included in the course.
Stock Market Prediction & Trading Bot using AI
Conditional Latent Autoregressive Recurrent Model for spatiotemporal learning
Text Extraction with POS Tagging and Deep Learning(LSTMs)
These are the notebook assignments from the deeplearning.ai Tensorflow course on coursera.
Transformers + Mambas + LSTMS All in One Model
masters thesis on deep learning methods for speech enhancement
This repository contains the work done as part of my B.Tech Project
Sentimental Analysis of Movie Reviews Using Pytorch
Uses deep learning to translate Indian Sign Language in real-time
Emotions dataset for NLP classification tasks.
This repo contains all of my submissions to Kaggle competitions or datasets
Built a stock prediction program in which the user can pick any company available on Yahoo! Finances and be able to predict the closing price of the stock based on the set date with high accuracy.
Course Repository for ELL881 (Special Topics:Modern Natural Language Processing), 6th Semester, 2023, IITD
Predicted the price movement of the Dow Jones, Apple, and Microsoft with 60% accuracy by experimenting with more than 100 ensembles of long-short term memory networks (LSTMs). NLP techniques were explored such as sentiment analysis to use as features in the model.
Generation of Simpsons tv scripts using Recurrent neural networks using Tensorflow.
Generated pseudo text using LSTMs (Long Short Term Memory networks) and GPT-2, evaluated how close this machine-generated text is to human-generated text by checking if they follow statistical features followed by human-generated text such as Zipf’s and Heap’s Laws for Words
Includes examples of code I have written both independently and collaboratively.
Predicting missing metadata with recurrent neural network (RNNs) based entity extraction
The idea is to develop a machine learning program to identify when an article might be fake news.
Music Prediction Project for the CS 6355 Structured Prediction Spring 2021 class at the University of Utah