borb-google-colab-examples
machine_learning_basics
Our great sponsors
| borb-google-colab-examples | machine_learning_basics | |
|---|---|---|
| 3 | 5 | |
| 10 | 4,205 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | 3 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 only | 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.
borb-google-colab-examples
machine_learning_basics
-
Bayesian linear regression in (plain) Python
A while back I open sourced a repository implementing fundamental machine learning algorithms in Python, along with the most important theoretical information. I originally created the repository for myself when preparing for AI residency interviews. You can find the original Reddit post here.
- Bayesian linear regression in Python
What are some alternatives?
ta - Technical Analysis Library using Pandas and Numpy
Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.
Face-Mask-Detection - Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras
100-Days-Of-ML-Code - 100 Days of ML Coding
pythoncode-tutorials - The Python Code Tutorials
mango - Parallel Hyperparameter Tuning in Python
borb - borb is a library for reading, creating and manipulating PDF files in python.
trulens - Evaluation and Tracking for LLM Experiments
go-wkhtmltopdf - Go bindings for wkhtmltopdf and high-level HTML to PDF conversion interface
rmi - A learned index structure
chromic_pdf - Convenient HTML to PDF/A rendering library for Elixir based on Chrome & Ghostscript
PyImpetus - PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features