The result is based on ratio of number of commits and code additions from initial and final time ranges.
Initial time range – from 5 Jul, 2023 to 5 Oct, 2023
Final time range – from 5 Apr, 2024 to 5 Jul, 2024
Additions and deletions stats are not available for this repository due to GitHub API limitations.
It is basically a number of most active contributors responsible for 80% of contributions.
Bus factor tries to assess "What happens if a key member of the team is hit by a bus?". The more there are key members, the lower the risk.
The JordiCorbilla/stock-prediction-deep-neural-learning repository has a bus factor of 1.
High risk, a lot of knowledge concentrated in a few people
Bus factor was measured on 14 Aug 2024
The JordiCorbilla/stock-prediction-deep-neural-learning GitHub repository is a Python project that predicts stock prices using Deep Learning Neural Networks with TensorFlow.
The repository is public and does not have many stars, indicating that it may not have been viewed or used by many other developers. The code appears to be up-to-date since the last commit was made reasonably recently.
The repository is self-contained and does not seem to rely on external services other than those required by the code itself (such as Tensorflow), making it easy to clone and run for learning purposes. There are no contributing guidelines, suggesting that the owner does not actively seek contributions.
Features:
Potential limitations:
There is a lack of engagement and contribution from other developers.
This code can be useful for anyone interested in financial predictions and applications of deep learning in predicting time series data. However, it shouldn't be used for real stock market investments without proper understanding and enhancements.
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