Time-Series-Forecasting-Using-LSTM VS pytorch-seq2seq

Compare Time-Series-Forecasting-Using-LSTM vs pytorch-seq2seq and see what are their differences.

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Time-Series-Forecasting-Using-LSTM pytorch-seq2seq
1 3
13 5,150
- -
1.8 5.4
about 1 year ago 3 months ago
Jupyter Notebook Jupyter Notebook
- MIT License
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Time-Series-Forecasting-Using-LSTM

Posts with mentions or reviews of Time-Series-Forecasting-Using-LSTM. We have used some of these posts to build our list of alternatives and similar projects.

pytorch-seq2seq

Posts with mentions or reviews of pytorch-seq2seq. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-29.

What are some alternatives?

When comparing Time-Series-Forecasting-Using-LSTM and pytorch-seq2seq you can also consider the following projects:

cryptocurrency-price-prediction - Cryptocurrency Price Prediction Using LSTM neural network

tensor2tensor - Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

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

poolformer - PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)

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

Behavior-Sequence-Transformer-Pytorch - This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf

TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0

ru-dalle - Generate images from texts. In Russian

sequitur - Library of autoencoders for sequential data

awesome-speech-recognition-speech-synthesis-papers - Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)

pytorch-GAT - My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

Deep-Learning-Papers-Reading-Roadmap - Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!