# khuangaf/CryptocurrencyPrediction

Predict Cryptocurrency Price with Deep Learning

Repository: https://github.com/khuangaf/CryptocurrencyPrediction
Canonical: https://ross.abutalabs.com/products/cryptocurrencyprediction
Homepage: https://blog.goodaudience.com/predicting-cryptocurrency-price-with-tensorflow-and-keras-e1674b0dc58a
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: deep-learning, machine-learning, cryptocurrency, bitcoin, cnn, lstm, gru, sklearn, final-year-project
Last push: 2023-03-10T06:55:12+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3279, "days_push": 1272, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1058, forks 362 (observed 2026-08-28T04:03:25.364202+00:00)

## What it is
A Jupyter Notebook-based deep learning project that predicts Bitcoin prices using CNN, LSTM, and GRU models built with Keras and TensorFlow. It includes data collection from Poloniex, preprocessing, model training, and validation result plotting.

## Use cases
- predict bitcoin price with deep learning
- learn lstm and gru for time series forecasting
- build a cnn model for cryptocurrency price prediction
- collect historical crypto data from poloniex for training
- compare rnn and cnn models on financial time series
- tutorial project for keras and tensorflow time series

## When to choose
- learning deep learning on time series with a small, readable codebase
- reproducing a classic CNN/LSTM/GRU price prediction experiment
- starting a student project on cryptocurrency forecasting

## When to avoid
- building a production trading system - models underperform a simple lag baseline
- working with modern Python - it targets Python 2.7 and old TensorFlow/Keras versions
- needing live data pipelines or up-to-date exchange APIs

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning, data-science
- domain: deep-learning, machine-learning, fintech
- platform: python
- tags: bitcoin, lstm, gru, cnn, keras, tensorflow, price-prediction, time-series, jupyter-notebook, final-year-project, cryptocurrency

## Member repositories
- khuangaf/CryptocurrencyPrediction (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:25.364202+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:57:47.595782+00:00, confidence not recorded.
  - readme: https://github.com/khuangaf/CryptocurrencyPrediction (fetched 2026-08-28T04:03:25.364202+00:00, sha bf83d2625474)
- Data as of 2026-08-30T08:39:29.467469+00:00.