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14 search results found

Flow Forecast ⭐ 1,759

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

Getting Things Done With Pytorch ⭐ 873

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

Video Classification ⭐ 498

Tutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101

Accel Brain Code ⭐ 289

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language proces

Nlp De Cero A Cien ⭐ 135

Curso práctico: NLP de cero a cien 🤗

Sluice Networks ⭐ 119

Code for Sluice networks: Learning what to share between loosely related tasks

Transfer Learning Text Tf ⭐ 74

Tensorflow implementation of Semi-supervised Sequence Learning (https://arxiv.org/abs/1511.01432)

Dl_notebooks ⭐ 42

This repo contains all the notebooks mentioned in blog.

Udacity Cvnd Projects ⭐ 34

My solutions to the projects assigned for the Udacity Computer Vision Nanodegree

Ntua Slp Wassa Iest2018 ⭐ 18

Deep-learning Transfer Learning models of NTUA-SLP team submitted at the IEST of WASSA 2018 at EMNLP 2018.

Academic Paper Title Recommendation ⭐ 9

Supervised text summarization (title generation/recommendation) based on academic paper abstracts, with Seq2Seq LSTM and the power of Transfer Learning and T5.

Udacity Deep Learning Nanodegree ⭐ 8

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.

Deep Learning Nd ⭐ 7

Projects and exercises for the Deep Learning Nanodegree

Security Intelligence On Exchanged Multimedia Messages Based On Deep Learning ⭐ 6

Deep learning (DL) approaches use various processing layers to learn hierarchical representations of data. Recently, many methods and designs of natural language processing (NLP) models have shown significant development, especially in text mining and analysis. For learning vector-space representations of text, there are famous models like Word2vec, GloVe, and fastText. In fact, NLP took a big step forward when BERT and recently GTP-3 came out. Deep Learning algorithms are unable to deal with te

Bert_imdb ⭐ 5

A repo for NLP model Bert.

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