Titlebook: Data Analytics and Machine Learning; Navigating the Big D Pushpa Singh,Asha Rani Mishra,Payal Garg Book 2024 The Editor(s) (if applicable)

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Performing Citizenship: Acts of Writingtoday, and they have garnered a lot of attention for their ability to influence organizational decision-making. With the use of these technologies, firms are able to provide valuable data and obtain answers that will improve their performance and provide them with a competitive advantage. A customer

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Building Predictive Models with Machine Learning,data into actionable insights. Key themes include the selection of an appropriate machine learning model tailored to specific problems, mastering the art of feature engineering to refine raw data into informative features aligned with chosen algorithms, and the iterative process of model training an

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Stream Data Model and Architecture,usly generated at a bang-up velocity. Because of integral dynamical features of big data, it is hard to apply existing working models directly on big data streams. The solution of this limitation is data streaming. A modern-day data streaming architecture allows taking up, operating and analyzing hi

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Applying Data Analytics and Time Series Forecasting for Thorough Ethereum Price Prediction,hich works on the Blockchain technology. This has proved to be a new topic of research for computer science. However, these currencies are volatile in nature and their forecasting can be really challenging as there are dozens of cryptocurrencies in use all around the world. This chapter uses the tim

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Practical Implementation of Machine Learning Techniques and Data Analytics Using R,s customers to optimize their sales strategies which mainly includes focusing more on valuable customers which is based on the amount of purchase made by customer rather than the traditional way of recommending a product. In the modern recommendation systems different parameters are synthesized for

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