Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis | Stock Market Prediction Web App | Predictive Analytics library

 by   kaushikjadhav01 Python Version: Current License: No License

kandi X-RAY | Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis Summary

kandi X-RAY | Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis Summary

Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis is a Python library typically used in Analytics, Predictive Analytics applications. Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
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            kandi-support Support

              Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis has a low active ecosystem.
              It has 378 star(s) with 153 fork(s). There are 23 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 16 open issues and 6 have been closed. On average issues are closed in 74 days. There are 3 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis is current.

            kandi-Quality Quality

              Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis has 0 bugs and 0 code smells.

            kandi-Security Security

              Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis saves you 14797 person hours of effort in developing the same functionality from scratch.
              It has 29566 lines of code, 12 functions and 30 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis and discovered the below as its top functions. This is intended to give you an instant insight into Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis implemented functionality, and help decide if they suit your requirements.
            • The main function for inserting data into a table .
            • Add the headers to the response .
            • Initialize the object .
            • Show index . html .
            Get all kandi verified functions for this library.

            Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis Key Features

            No Key Features are available at this moment for Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis.

            Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis Examples and Code Snippets

            No Code Snippets are available at this moment for Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis.

            Community Discussions

            QUESTION

            will TensorFlow utilize GPU for predictive Analysis?
            Asked 2020-Nov-21 at 21:35

            GPU is good for parallel computing but the problem is some machine learning libraries don't utilize the GPU, unless that machine learning based on image processing or some sort of graphics processing, what if I am using machine learning for predictive Analytics? do libraries like TensorFlow utilize the GPU? or they use only CPU? or can I choose which processing unit to use? whats the deal here?

            note: predictive Analysis requires no graphics processing.

            ...

            ANSWER

            Answered 2020-Nov-21 at 21:35
            The short answer: yes, it will! The slightly longer answer:

            The computation that happens in the GPU in any of the machine learning frameworks that support GPUs is not limited to graphical processing. For instance, if your model is a simple logistic regression, a framework such as TensorFlow will run it on the GPU if properly configured.

            The advantage of GPUs for machine learning is that training big neural networks benefits greatly from the high level of parallelism that the GPUs offer.

            If you want to know more about this, I'd recommend you start here or here.

            some things to consider:
            • how much a model will benefit from running in the GPU will depend on how much it will benefit from parallel computation in general.
            • Deep Learning models can be applied to predictive analytics, as well as more classical machine learning models. Bear in mind that neural nets are possibly the category of models that will benefit inherently from the GPU (see links above).
            • Even though running models using GPUs (or even more specialised hardware) can bring benefits, I would suggest that you don't choose a framework and, especially, don't choose an algorithm based solely on the fact that it will benefit from parallelism, but rather look at how appropriate a given algorithm is for the data you have.

            Source https://stackoverflow.com/questions/64948197

            QUESTION

            Restructuring Pandas Dataframe for large number of columns
            Asked 2020-Nov-01 at 19:39

            I have a pandas dataframe which is a large number of answers given by users in response to a survey and I need to re-structure it. There are up to 105 questions asked each year, but I only need maybe 20 of them.

            The current structure is as below.

            What I want to do is re-structure it so that the row values become column names and the answer given by the user is then the value in that column. In a picture (from Excel), what I want is the below (I know I'll need to re-name my columns, but that's fine once I can create the structure in the first place):

            Is it possible to re-structure my dataframe this way? The outcome of this is to use some predictive analytics to predict a target variable, so I need to re-strcture before I can use Random Forest, kNN, and so on.

            ...

            ANSWER

            Answered 2020-Nov-01 at 19:39

            You might want try pivoting your table:

            Source https://stackoverflow.com/questions/64630691

            QUESTION

            Display data from two json files in react native
            Asked 2020-May-17 at 23:55

            I have js files Dashboard and Adverts. I managed to get Dashboard to list the information in one json file (advertisers), but when clicking on an advertiser I want it to navigate to a separate page that will display some data (Say title and text) from the second json file (productadverts). I can't get it to work. Below is the code for the Dashboard and next for Adverts. Then the json files

            ...

            ANSWER

            Answered 2020-May-17 at 23:55

            The new object to get params in React Navigation 5 is:

            Source https://stackoverflow.com/questions/61859411

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

            Vulnerabilities

            No vulnerabilities reported

            Install Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis

            Clone the repo. Download and install XAMPP server from https://www.apachefriends.org/download.html and start Apache and MySql servers
            Open phpmyadmin by visiting http://localhost/phpmyadmin/ and go to User Accounts -> Add a User, give username and password as admin and click on Check All next to Global Privileges and hit Go
            Next, create a new database named wordpress
            Select the wordpress database and click on Import and select the wordpress.sql file from the repo.
            Download my wordpress website zip file from here
            Extract the above zip file in xampp/htdocs folder
            Go to command prompt, change directory to directory of repository and type pip install -r requirements.txt
            To run app, type in command prompt, python main.py
            Open your web browser and go to http://localhost/www and click on the wordpress folders to access the web app
            Wordpress Admin Panel is available at: http://localhost/www/wordpress-5.6.2/wordpress/wp-admin

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            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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            gh repo clone kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis

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