A platform for analyzing the stock market using information from major market indices.
With the help of artificial intelligence, the platform uses information from major market indices to help users make a decision on whether to make a deal. The project solves the task of analyzing the securities market and provides users with tools to make decisions on making deals at the best time.
Challenges
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Training Classroom: One of the challenges was to create a functional and efficient training classroom on the platform. The training classroom provides users with access to up-to-date video news, expert commentaries and analyses related to the securities market. We faced the need to integrate video lecture streams, ensure high download speeds and compatibility with various devices for user convenience.
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Excel table: Another challenge was to develop the ability to utilise Excel tables on the platform. This allows users to import their own tables of securities data or create new tables to analyse and track their investments. We faced the challenges of processing and formatting data from Excel files, ensuring the security and privacy of the information.
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Integrating artificial intelligence to analyse securities: One of the key challenges was to develop and integrate artificial intelligence on the platform that is able to analyse market index data and provide recommendations to the user on the best time to make a trade. This involved processing large volumes of data, training machine learning models and creating predictive algorithms.
Solutions
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Working with video platforms: Using video platforms.
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Video streams: Optimising video streams.
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Integrating with libraries: Integrating with Excel reading libraries.
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Data processing and analysis.
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Exporting data to Excel.
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Machine Learning: Using machine learning algorithms.
What We Have
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Users now have access to the latest video news, comments and analyses related to the securities market.
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Users now have the ability to comment on videos and communicate with other community members via chats or comments.
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The functionality of filtering, sorting and other operations on data in tables was implemented.
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Users were given the ability to import their own securities data tables or create new tables to analyse and track their investments.
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Artificial intelligence successfully analysed market index data and provided recommendations to users on the best time to make a trade.
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Large volumes of data were processed and machine learning algorithms were applied to achieve high accuracy of forecasts.