awesome-bigdata
datascience
| awesome-bigdata | datascience | |
|---|---|---|
| 3 | 4 | |
| 12,861 | 4,130 | |
| - | - | |
| 1.0 | 8.2 | |
| 25 days ago | 4 days ago | |
| MIT License | Creative Commons Zero v1.0 Universal |
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.
awesome-bigdata
datascience
- Datasciene Libraries for Python
- Datascience Libraries for Python
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Good resources for learning ML with time series in Python? Some links I've found, but looking for canonical resources.
This GitHub repo maintains a good list of resources. Check out the "Time Series" section. https://github.com/r0f1/datascience
- Opinionated List of Data Science Libraries for Python
What are some alternatives?
tensorbase - TensorBase is a new big data warehousing with modern efforts.
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
NEPSE-Data-Visualizer-with-Streamlit - This is a repository to do data visualization of Nepal Stock Exchange data.
mlnotify - 🔔 No need to keep checking your training - just one import line and you'll know the second it's done.
yt-channels-DS-AI-ML-CS - A comprehensive list of 180+ YouTube Channels for Data Science, Data Engineering, Machine Learning, Deep learning, Computer Science, programming, software engineering, etc.
machine-learning-for-software-engineers - A complete daily plan for studying to become a machine learning engineer.
ActivitySchema - Repository for the ActivitySchema spec and supporting materials
Kats - Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
awesome-dataviz - :chart_with_upwards_trend: A curated list of awesome data visualization libraries and resources.
mlreef - The collaboration workspace for Machine Learning
data-science-with-ruby - Practical Data Science with Ruby based tools.
darts - A python library for user-friendly forecasting and anomaly detection on time series.