Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
scripts used for neural decoding of single and multi unit auditory cortex data
Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massive Transpose extrapolation problem in onnx-tensorflow (onnx-tf). I don't need a Star, but give me a pull request.
Deep convolutional and LSTM feature extraction approach with 784 features.
A bangla chatbot using bidirectional lstm
This project develops a long short-term memory-based (LTSM-based) deep learning model to predict short-term transit passenger volume on metro routes in Medelllín, Colombia.
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.
Seq2SeqSharp is a tensor based fast & flexible deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, different network types (Transformer, LSTM, BiLSTM and so on), multi-GPUs supported, cross-platforms (Windows, Linux, x86, x64, ARM), multimodal model for text and images and so on.
The practitioner's forecasting library
Paint2code - a lightweight tool designed to transform your hand-drawn sketches into functional HTML code.
Fast-API base StockSeer-API uses different machine learning alogs to forecast closing stock prices.
BitPredictor - A cutting-edge machine learning-based solution for predicting cryptocurrency prices. Harnessing the power of advanced algorithms and data analysis techniques, this system aims to provide accurate and timely forecasts for Bitcoin and other cryptocurrencies.
Jupyter notebooks for the Deep Learning course that is held at FEI, VSB-TU Ostrava
Internship project at Institute for Plasma Research for Predicting Turbulent Flows using DNNs.
A demonstration application for LSTM based time series forecasting with NOAA temperature data. Dataset organized with MongoDB, model performance analyzed with SQL (MySQL), REST API created with FastAPI, and application containerized with Docker
Parallel Reverse Mode Automatic Differentiation in C# for Custom Neural Network Development
Chatbot for UC Main
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