12 Weeks, 24 Lessons, AI for All!

Open-source AI library (audio to text, simple NLP and algorithms)

Exercises on Machine Learning

Code for "Sufficient conditions for offline reactivation in recurrent neural networks" (ICLR 2024)

Sentiment analysis of movie comments using the PyTorch and Django frameworks.

This project is a knowledge test on time series applied to pollution analysis. This exercise has been carried out with a series of restrictions on the dataset. The objective is to use machine learning techniques, specifically recurrent neural networks.

Hello! We are an international group of students researching deep learning applications for Alzheimer's disease. We aim to introduce a better model for AD diagnosis. Our names are Hugo Jal Hernández, Basit Oliyide, Parth Parikh & Ravi Shah.

Curse-of-memory phenomenon of RNNs in sequence modelling

This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.

Chinese corpus sentiment analysis. 谭松波酒店评论中文文本情感分析

This is the code related to my MSc thesis at the Norwegian University of Science and Technology (NTNU). The MSc program is Electronic system design and innovation with a specialization in signal processing. The goal of this thesis is to explore and compare the state of the art solution to more traditional models for time series generation.

Official PyTorch implementation of the CVPR 2024 paper: State Space Models for Event Cameras (Spotlight).

Design of target-focused libraries by probing continuous fingerprint space with recurrent neural networks. The repository accompanies a research paper which is currently under review (08.04.24)

Detectify is a deep learning system that detects AI-generated fake videos (deepfakes) using CNN and LSTM-based RNNs. Trained on datasets like Face-Forensic++, Deepfake Detection Challenge, and Celeb-DF, Detectify offers real-time video manipulation detection to combat misinformation and misuse of deepfake technology.

We investigate the effectiveness of Recurrent Neural Networks (RNNs) in financial text data sentiment analysis, emphasizing Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM).

A Long Term Training On Artificial Intelligence

Deep Learning with Numpy and TensorFlow

NeuroFlame: Neural Network Fast Learning And Modeling Engine

Sentimental Analysis