Time-Series-Forecasting-Using-LSTM
cryptocurrency-price-prediction
Our great sponsors
| Time-Series-Forecasting-Using-LSTM | cryptocurrency-price-prediction | |
|---|---|---|
| 1 | 2 | |
| 13 | 555 | |
| - | - | |
| 1.8 | 0.0 | |
| about 1 year ago | over 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Time-Series-Forecasting-Using-LSTM
cryptocurrency-price-prediction
-
Help with Jupyter notebook for crypto price prediction
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 (https://github.com/abhinavsagar/cryptocurrency-price-prediction/issues/1) so the results are just not there.
What are some alternatives?
pytorch-seq2seq - Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
AI-Expert-Roadmap - Roadmap to becoming an Artificial Intelligence Expert in 2022
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
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
sc2eval - LSTM-based machine learning solution for evaluation of strategic position in Starcraft II.