692 Open source projects that are alternatives of or similar to Sequence-Models-coursera

Deep Learning Specialization by Andrew Ng on Coursera - My Completed Coursework Repo - All 5 Courses

🧠👨‍💻Deep Learning Specialization • Lecture Notes • Lab Assignments

分别使用rnn/cnn/rcnn来实现根据患者描述，进行疾病诊断

This is Andrew NG Coursera Handwritten Notes.

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

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

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

吴恩达《深度学习》系列课程笔记及代码 | Notes in Chinese for Andrew Ng Deep Learning Course

Notes and Assignments for Andrew Ng's Machine Learning - Python3 code

Easy-to-use Deep LSTM Neural Network to generate song sounds like containing improvisation.

Stanford University - Machine Learning by Andrew Ng

CPU and GPU implementations of some 2D RNN layers

Programming assignments, labs and quizzes from all courses in the Coursera AI for Medicine Specialization offered by deeplearning.ai

Natural Language Processing with TensorFlow, published by Packt

A siamese LSTM to detect sentence/question pairs.

A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.

Deep Learning

深度学习笔记

该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。

Deep learning driven jazz generation using Keras & Theano!

This is the Python implementation of the programming assignments in Andrew Ng's online machine-learning course.

Recurrent Additive Networks for Tensorflow

基於DA-RNN之DSTP-RNN論文試做(Ver1.0)

Enhanced BiLSTM Inference Model for Natural Language Inference

ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

Recurrent Neural Networks (RNN, GRU, LSTM) and their Bidirectional versions (BiRNN, BiGRU, BiLSTM) for word & character level language modelling in Theano

End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

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

Reasoning Over Knowledge Graph Paths for Recommendation

UrbanSound classification using Convolutional Recurrent Networks in PyTorch

Sign Language Gesture Recognition From Video Sequences Using RNN And CNN

Nested LSTM Cell

Efficient, transparent deep learning in hundreds of lines of code.

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

Haste: a fast, simple, and open RNN library

This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.

deeplearning.ai , By Andrew Ng, All video link

End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

Notes for Deep Learning Specialization Courses led by Andrew Ng.

Homework about Machine Learning of Coursera taught by andrew ng

Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems

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

This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.

Hands-on in-person workshop for Deep Learning with TensorFlow

RNN-LSTM that learns passwords from a starting list

LSTM based human activity recognition using smart phone sensor dataset

GPU/CPU (CUDA) Implementation of "Recurrent Memory Array Structures", Simple RNN, LSTM, Array LSTM..

Deep Learning Specialization Course by Coursera. Neural Networks, Deep Learning, Hyper Tuning, Regularization, Optimization, Data Processing, Convolutional NN, Sequence Models are including this Course.

Train LSTM to writer novel (HongLouMeng here) in Pytorch.

Deeplearning.ai - Andrew Ng - Coursera

Electric load forecast using Long-Short-Term-Memory (LSTM) recurrent neural network

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

Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng

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).

A cute multi-layer LSTM that can perform like a human 🎶

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch. Based on code of https://github.com/karpathy/char-rnn. Support Chinese and other things.

📓 Notes for Andrew Ng's courses on deep learning

Online Hand Writing Recognition using BLSTM

Hand Written course notes of Deep Learning Specialization by Andrew NG on Coursera

基於關聯式新聞提取方法之雙階段注意力機制模型用於股票預測