Stock-Prediction | stock technical indicators and deep LSTM | Business library

by farismismar Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Stock-Prediction Summary

Stock-Prediction is a Python library typically used in Web Site, Business, Deep Learning, Keras, Neural Network applications. Stock-Prediction has no bugs, it has no vulnerabilities and it has low support. However Stock-Prediction build file is not available. You can download it from GitHub.

This file uses deep LSTM and various financial technical indicators functions to predict stock price. LSTM is implemented using Keras with TensorFlow in the backend.

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Quality

Security

License

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Support

Stock-Prediction has a low active ecosystem.

It has 13 star(s) with 9 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 51 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Stock-Prediction is current.

Quality

Stock-Prediction has 0 bugs and 0 code smells.

Security

Stock-Prediction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Stock-Prediction code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Stock-Prediction does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

Stock-Prediction releases are not available. You will need to build from source code and install.

Stock-Prediction has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed Stock-Prediction and discovered the below as its top functions. This is intended to give you an instant insight into Stock-Prediction implemented functionality, and help decide if they suit your requirements.

Run a prediction on a time series
Convenience function to perform chanin
Convenience function for the Chanikin flow
Feature engineering method

Get all kandi verified functions for this library.

Stock-Prediction Key Features

No Key Features are available at this moment for Stock-Prediction.

Stock-Prediction Examples and Code Snippets

No Code Snippets are available at this moment for Stock-Prediction.

Community Discussions

Trending Discussions on Stock-Prediction

How to upload files to Amazon EMR?

QUESTION

How to upload files to Amazon EMR?

Asked 2021-Apr-13 at 08:00

My code is as follows:

...

ANSWER

Answered 2021-Apr-13 at 08:00

Your understanding is correct.

--files argument is uploading files to executors only.

See this in the spark documentation

file: - Absolute paths and file:/ URIs are served by the driver’s HTTP file server, and every executor pulls the file from the driver HTTP server.

You can read more about this at advanced-dependency-management

Now coming back to your second question

How can I upload to master?

There is a concept of bootstrap-action in EMR. From the official documentation it means the following:

You can use a bootstrap action to install additional software or customize the configuration of cluster instances. Bootstrap actions are scripts that run on cluster after Amazon EMR launches the instance using the Amazon Linux Amazon Machine Image (AMI). Bootstrap actions run before Amazon EMR installs the applications that you specify when you create the cluster and before cluster nodes begin processing data.

How do I use it in my case?

While spawning the cluster you can specify your script in BootstrapActions JSON Something like the following along with other custom configurations:

Source https://stackoverflow.com/questions/67042056

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Stock-Prediction

You can download it from GitHub.
You can use Stock-Prediction like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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