Created on 3rd May 2023
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Stock investments provide one of the highest returns in the market. Even though they are volatile in nature, one can visualise share prices and other statistical factors which helps the keen investors carefully decide on which company they want to spend their earnings on.
Challenges in developing a stock predicting project using the Dash library include performance and scalability issues with large datasets, ensuring real-time updates for dynamic data, designing an intuitive user interface, and implementing robust model training and evaluation. To address these challenges, optimize code for efficiency, employ asynchronous programming techniques for real-time updates, focus on clean and user-friendly UI design using Dash's components and styling options, and utilize reliable methodologies for model training and evaluation. By overcoming these challenges, you can create a powerful stock predicting project that provides accurate insights and a seamless user experience.
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