lambda-packs VS external_documentation_redirect

Compare lambda-packs vs external_documentation_redirect and see what are their differences.

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lambda-packs external_documentation_redirect
1 1
1,106 3
- -
4.0 5.5
6 months ago 11 months ago
Python HTML
MIT License GNU Affero General Public License v3.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

lambda-packs

Posts with mentions or reviews of lambda-packs. We have used some of these posts to build our list of alternatives and similar projects.

external_documentation_redirect

Posts with mentions or reviews of external_documentation_redirect. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing lambda-packs and external_documentation_redirect you can also consider the following projects:

equilib - 🌎→🗾Equirectangular (360/panoramic) image processing library for Python with minimal dependencies only using Numpy and PyTorch

data-analytics-project-template - A python project starter template for data-analytics and data-science.

thinc - 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries

Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials - A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

mlcourse.ai - Open Machine Learning Course

einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

docker-data-science - Docker image with Data Science tools.

Photomosaic-Creator - This script allows you to create a photomosaic from a set of images.

qubiter - Python tools for reading, writing, compiling, simulating quantum computer circuits. Includes numpy and tensorflow backends. “Quantum Space, the final frontier. These are the voyages of the starship Qubiter. Its five-year mission: to explore strange new worlds, to seek out new life and new civilizations, to boldly go where no man has gone before.”