cryptocurrency-price-prediction VS Time-Series-Forecasting-Using-LSTM

Compare cryptocurrency-price-prediction vs Time-Series-Forecasting-Using-LSTM and see what are their differences.

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cryptocurrency-price-prediction Time-Series-Forecasting-Using-LSTM
2 1
493 3
- -
0.0 2.6
over 1 year ago 9 months ago
Jupyter Notebook Jupyter Notebook
MIT License -
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Posts with mentions or reviews of cryptocurrency-price-prediction. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-04.
  • Help with Jupyter notebook for crypto price prediction
    2 projects | | 4 Mar 2021
    Hey. This isn't really a predictor or forecaster in any sense, since the independent variables (X) are not knowable ahead of time. In fact, they include some serious data leakage such as the day's high and low, which will only be known at close (which is what it predicted). Also, the code to show the predictions is wrong, and essentially just shows the training data shifted forward ( so the results are just not there.
    2 projects | | 4 Mar 2021


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.

We haven't tracked posts mentioning Time-Series-Forecasting-Using-LSTM yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing cryptocurrency-price-prediction and Time-Series-Forecasting-Using-LSTM you can also consider the following projects:

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

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

AI-Expert-Roadmap - Roadmap to becoming an Artificial Intelligence Expert in 2022

machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.

spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python

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

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

LSTM-Human-Activity-Recognition - Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

artificial-intelligence-and-machine-learning - A repository for implementation of artificial intelligence algorithm which includes machine learning and deep learning algorithm as well as classical AI search algorithm