Deep_Learning_Machine_Learning_Stock
ML-Workspace
| Deep_Learning_Machine_Learning_Stock | ML-Workspace | |
|---|---|---|
| 48 | 7 | |
| 1,149 | 3,329 | |
| - | 0.6% | |
| 6.1 | 2.7 | |
| 2 months ago | 6 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
Deep_Learning_Machine_Learning_Stock
- Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:1017.0
- Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:924.0
- Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:792.0
- Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:729.0
- Deep-Learning-Machine-Learning-Stock: curated list of notebooks for machine learning models. Start with very simple linear models to more advanced reinforcement learning type of models. Problem with this repo is that the library version numbers may b
ML-Workspace
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[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
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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)
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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
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[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?
tsfresh - Automatic extraction of relevant features from time series:
JupyterLab - JupyterLab computational environment.
bulbea - :boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
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
FinanceDataReader - Financial data reader [Moved to: https://github.com/FinanceData/FinanceDataReader]
keytotext - Keywords to Sentences
TradingGym - Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
deltapy - DeltaPy - Tabular Data Augmentation (by @firmai)
Code-Server - VS Code in the browser
DataScienceProjects
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)