Analysis and Visualization of Discrete Data by Koji Koyamada (.PDF)

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File Size: 53.9 MB

Analysis and Visualization of Discrete Data Using Neural Networks by Koji Koyamada
Requirements: .PDF reader, 53.9 MB
Overview: This book serves as a comprehensive step-by-step guide on data analysis and statistical analysis. It covers fundamental operations in Excel, such as table components, formula bar, and ribbon, and introduces visualization techniques and PDE derivation using Excel. It also provides an overview of Google Colab, including code and text cells, and explores visualization and Deep Learning applications. Key features of the book include topics like statistical analysis, regression analysis, optimization, correlation analysis, and neural networks. It adopts a practical approach by providing examples and step-by-step instructions for learners to apply the techniques to real-world problems. The book also highlights the strengths and features of both Excel and Google Colab, allowing learners to leverage the capabilities of each platform. The clear explanations of concepts, visual aids, and code snippets aid comprehension help learners understand the principles of data analysis and statistical analysis. Overall, this book serves as a valuable resource for professionals, researchers, and students seeking to develop skills in data analysis, regression statistics, optimization, and advanced modeling techniques using Excel, Colab, and neural networks. Google Colaboratory (Colab for short) is a free cloud service provided by Google, where you can use the Jupyter notebook and Python to analyze data and build a model for Machine Learning.
Genre: Non-Fiction > Tech & Devices

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