tgjeon/TensorFlow-Tutorials-for-Time-Series resource
TensorFlow Tutorial for Time Series Prediction observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3748
- days_rel: n/a
- days_push: 3319
- n_releases_24m: 0
Adoption not part of the score
1101 stars · 411 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A collection of Jupyter notebook tutorials teaching time series prediction with TensorFlow using recurrent neural networks. It covers MNIST classification with RNNs, sine wave prediction with LSTM and Gaussian processes, and electricity price forecasting.
Use cases
- learn RNN basics with TensorFlow
- predict sine wave with LSTM
- forecast electricity prices with neural networks
- classify MNIST using recurrent networks
- tutorial on time series prediction in TensorFlow
When to choose
- learning RNN/LSTM concepts from worked notebooks
- studying classic TensorFlow r0.9-era code for historical reference
When to avoid
- building production models on modern TensorFlow (code targets r0.9 and is unmaintained)
- needing up-to-date APIs or maintained examples
Facets
learning-resource · maturity abandoned
machine-learning deep-learning machine-learning tutorials time-series python tensorflow rnn lstm jupyter-notebook time-series-forecasting deprecated
1 source
- readme: https://github.com/tgjeon/TensorFlow-Tutorials-for-Time-Series · fetched 2026-08-28 · 5656e3989e20
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| tgjeon/TensorFlow-Tutorials-for-Time-Series | main | 23 |
For agents
markdown · JSON · MCP: product_card(name="tgjeon/TensorFlow-Tutorials-for-Time-Series")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem