1594 Open source projects that are alternatives of or similar to Carrot

Anomaly detection for temporal data using LSTMs

brain.js is a GPU accelerated library for Neural Networks written in JavaScript.

Plain Stock Close-Price Prediction via Graves LSTM RNNs

Keras tutorial for beginners (using TF backend)

This is just a collection of projects that made during my DEEPLEARNING NANODEGREE by UDACITY

Neural machine translator for English2German translation.

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

Deep learning codes and projects using Python

OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

using rnn (lstm or gru) and ctc to convert line image into text, based on torch7 and warp-ctc

Tensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification

Multitask Deep Learning for Sentiment Analysis using Character-Level Language Model, Bi-LSTMs for POS Tag, Chunking and Unsupervised Dependency Parsing. Inspired by this great article https://arxiv.org/abs/1611.01587

News summarization using sequence to sequence model with attention in TensorFlow.

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Implementation of handwriting generation with use of recurrent neural networks in tensorflow. Based on Alex Graves paper (https://arxiv.org/abs/1308.0850).

A bidirectional LSTM with attention for multiclass/multilabel text classification.

Sarcasm detection on tweets using neural network

Machine learning, in numpy

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".

Malicious URL detector using keras recurrent networks and scikit-learn classifiers

Sequence analyzing using Recurrent Neural Networks (RNN) based on Keras

Lightweight C++11 library for building deep recurrent neural networks

Bitcoin price Prediction ( Time Series ) using LSTM Recurrent neural network

Some of the ML and DL related reading materials, research papers that I've read

A Python package for gender classification.

PyTorch tutorial for learners

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

Application of machine learning to the Coinbase (GDAX) orderbook

Keras implementation of Legendre Memory Units

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

OCR engine for all the languages

Komputation is a neural network framework for the Java Virtual Machine written in Kotlin and CUDA C.

TensorFlow and Deep Learning Tutorials

Sentiment Analysis on the First Republic Party debate in 2016 based on Python,NLTK and ML.

An Echo State Network module for PyTorch.

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

Augmenting word embeddings with their surrounding context using bidirectional RNN

Spying using Smartwatch and Deep Learning

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

Using LSTM network for time series forecasting

PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

Deep learning driven jazz generation using Keras & Theano!

TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction

Image Captioning: Implementing the Neural Image Caption Generator with python

Official PyTorch implementation of paper "A Hybrid Compact Neural Architecture for Visual Place Recognition" by M. Chancán (RA-L & ICRA 2020) https://doi.org/10.1109/LRA.2020.2967324

One Shot Learning using Memory-Augmented Neural Networks (MANN) based on Neural Turing Machine architecture in Tensorflow

[AAAI 2020] Modeling Personality with Attentive Networks and Contextual Embeddings

A Keras library for multi-step time-series forecasting.