Deep Learning Tools for Predicting Stock Market by Renuka Sharma(.PDF)

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File Size: 5 MB

Deep Learning Tools for Predicting Stock Market Movements by Renuka Sharma, Kiran Mehta
Requirements: .ePUB, .PDF reader, 14,5 MB
Overview: The book provides a comprehensive overview of current research and developments in the field of Deep Learning models for stock market forecasting in the developed and developing worlds. The book delves into the realm of Deep Learning and embraces the challenges, opportunities, and transformation of stock market analysis. Deep Learning helps foresee market trends with increased accuracy. With advancements in Deep Learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. The present study gives a comprehensive overview of the advancements and potential avenues in the realm of utilizing Deep Learning techniques for forecasting stock market trends. This study surveys the evolving landscape of Deep Learning methodologies employed in predicting stock price movements and offers insights into their effectiveness across various time frames and market conditions. The research delves into the multifaceted aspects of this field, encompassing architectures such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), and more recent transformer-based models.
Genre: Non-Fiction > Tech & Devices

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