mlcourse.ai VS napari

Compare mlcourse.ai vs napari and see what are their differences.

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mlcourse.ai napari
85 3
9,345 2,032
- 2.3%
3.4 9.7
3 months ago 1 day ago
Python Python
GNU General Public License v3.0 or later BSD 3-clause "New" or "Revised" License
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.

mlcourse.ai

Posts with mentions or reviews of mlcourse.ai. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-25.

napari

Posts with mentions or reviews of napari. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-13.

What are some alternatives?

When comparing mlcourse.ai and napari you can also consider the following projects:

glumpy - Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization

attractors - Package for simulation and visualization of strange attractors.

quaternion - Add built-in support for quaternions to numpy

concrete-numpy - Concrete-Numpy: A library to turn programs into their homomorphic equivalent.

hiitpi - A workout trainer Dash/Flask app that helps track your HIIT workouts by analyzing real-time video streaming from your sweet Pi using machine learning and Edge TPU..

GreyNSights - Privacy-Preserving Data Analysis using Pandas

Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many 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.

cupy - NumPy & SciPy for GPU

julia - The Julia Programming Language

WaveNCC - An app to compute the normalization coefficients of a given set of orthogonal 1D complex wave functions.