handson-ml
ML-Workspace
| handson-ml | ML-Workspace | |
|---|---|---|
| 1 | 7 | |
| 25,156 | 3,391 | |
| - | 0.5% | |
| 0.0 | 1.4 | |
| 11 months ago | about 2 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
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.
handson-ml
-
need a book recommendation for machine learning on python
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow is often recommended. You can check out the GitHub repo first: https://github.com/ageron/handson-ml
ML-Workspace
-
[D] I recently quit my job to start a ML company. Would really appreciate feedback on what we're working on.
Also check out: https://github.com/ml-tooling/ml-workspace, it a nice open source project with lots of packages ready to use.
- ML-Workspace
-
Coding for machine learning on Tab S8?
The other option - no reason why you couldn't host something on the desktop machine - web based IDE like R-Studio or Python - have a look at ml-workspace - https://github.com/ml-tooling/ml-workspace that runs in Docker and would provide interfaces for both Python and R, VSCode as well as a GPU accelerated variant for doing Tensorflow etc - either Windows or Linux can support Docker containers (Linux is less trouble apparently - I only have played with it in Linux personally)
-
Dynamically spin up VM (based on specific HTTPS request) and stop it once session is over?
It will be a web based IDE dev kit (like Jupyter Hub, or JupyterLab) if you are familiar with them)
- All-in-One Docker Based IDE for Data Science and ML
- Visual Studio Code now available as Web based editor for GitHub repos
-
[P] Install or update CUDA, NVIDIA Drivers, Pytorch, Tensorflow, and CuDNN with a single command: Lambda Stack
I'll stick with https://github.com/ml-tooling/ml-workspace, is a docker with all tools installed, also the option of using GPU, so I think is better than only for debian. This way anyone can use it.
What are some alternatives?
Spotify_Song_Recommender - This project leverages spotify's api and provided user playlists to create and tune a neural network model that generates song recommendations based off of song data in provided playlists.
JupyterLab - JupyterLab computational environment.
AeroPython - Classical Aerodynamics of potential flow using Python and Jupyter Notebooks
Gitpod - DEPRECATED since Gitpod 0.5.0; use https://github.com/gitpod-io/gitpod/tree/master/chart and https://github.com/gitpod-io/gitpod/tree/master/install/helm
Twitter-sentiment-analysis - A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.
keytotext - Keywords to Sentences
Machine-Learning-Specialization-Coursera - Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
python-machine-learning-book-3rd-edition - The "Python Machine Learning (3rd edition)" book code repository
Code-Server - VS Code in the browser
weightless_NN_decompression - Proof of concept for neural network decompression without storing any weights
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)