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A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis.Key FeaturesUse Microsoft's product Excel to build advanced forecasting models using varied examplesCover range of machine learning tasks such as data mining, data analytics, smart visualization, and moreDerive data-driven techniques using Excel plugins and APIs without much code requiredBook DescriptionWe have made huge progress in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Excel users, of all levels, can feel left behind by this innovation wave. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel. The book starts by giving a general introduction to machine learning, making every concept clear and understandable. Then, it shows every step of a machine learning project, from data collection, reading from different data sources, developing models, and visualizing the results using Excel features and offerings. In every chapter, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow. Different machine learning models are shown, tailored to the type of data to be analyzed. At the end of the book, the reader is presented with some advanced use cases using Automated Machine Learning, and artificial neural network, which simplifies the analysis task and represents the future of machine learning. What you will learnUse Excel to preview and cleanse datasetsUnderstand correlations between variables and optimize the input to machine learning modelsUse and evaluate different machine learning models from ExcelUnderstand the use of different visualizationsLearn the basic concepts and calculations to understand how artificial neural networks workLearn how to connect Excel to the Microsoft Azure cloudGet beyond proof of concepts and build fully functional data analysis flowsWho this book is forThis book is for data analysis, machine learning enthusiasts, project managers, and someone who doesn't want to code much for performing core tasks of machine learning. Each example will help you perform end-to-end smart analytics. Working knowledge of Excel is required.

Machine learning. --- Microsoft Excel (Computer file)

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Statistics --- Forecasting --- Microsoft Excel (Computer file)

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Dashboards (Management information systems) --- Accounting --- Microsoft Excel (Computer file)

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Business --- Electronic spreadsheets. --- Computer programs. --- Microsoft Excel (Computer file)

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Explore the aspects of financial modeling with the help of clear and easy-to-follow instructions and a variety of Excel features, functions, and productivity tips Key Features A non-data professional's guide to exploring Excel's financial functions and pivot tables Prepare various models for income and cash flow statements, and balance sheets Perform valuations and identify growth drivers with real-world case studies Book Description Financial modeling is a core skill required by anyone who wants to build a career in finance. Hands-On Financial Modeling with Microsoft Excel 2019 explores terminologies of financial modeling with the help of Excel. This book will provides you with an overview of the steps you should follow to build an integrated financial model. You will explore the design principles, functions, and techniques of building models in a practical manner. Starting with the key concepts of Excel, such as formulas and functions, you will learn about referencing frameworks and other advanced components for building financial models. Later chapters will help you understand your financial projects, build assumptions, and analyze historical data to develop data-driven models and functional growth drivers. The book takes an intuitive approach to model testing and covers best practices and practical use cases. By the end of this book, you will have examined the data from various use cases, and have the skills you need to build financial models to extract the information required to make informed business decisions. What you will learn Identify the growth drivers derived from processing historical data in Excel Use discounted cash flow (DCF) for efficient investment analysis Build a financial model by projecting balance sheets and profit and loss Apply a Monte Carlo simulation to derive key assumptions for your financial model Prepare detailed asset and debt schedule models in Excel Discover the latest and advanced features of Excel 2019 Calculate profitability ratios using various profit parameters Who this book is for This book is for data professionals, analysts, traders, business owners, and students, who want to implement and develop a high in-demand skill of financial modeling in their finance, analysis, trading, and valuation work. This book will also help individuals that have and don't have any experience in data and stats, to get started with building financial models. The book assumes working knowledge with Excel. Downloading the ...

Corporations --- Finance --- Mathematical models. --- Data processing. --- Microsoft Excel (Computer file)