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Python Business Intelligence Cookbook

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Release : 2015-12-22
Genre : Computers
Kind : eBook
Book Rating : 667/5 ( reviews)

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Book Synopsis Python Business Intelligence Cookbook by : Robert Dempsey

Download or read book Python Business Intelligence Cookbook written by Robert Dempsey. This book was released on 2015-12-22. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the computational power of Python with more than 60 recipes that arm you with the required skills to make informed business decisions About This Book Want to minimize risk and optimize profits of your business? Learn to create efficient analytical reports with ease using this highly practical, easy-to-follow guide Learn to apply Python for business intelligence tasks—preparing, exploring, analyzing, visualizing and reporting—in order to make more informed business decisions using data at hand Learn to explore and analyze business data, and build business intelligence dashboards with the help of various insightful recipes Who This Book Is For This book is intended for data analysts, managers, and executives with a basic knowledge of Python, who now want to use Python for their BI tasks. If you have a good knowledge and understanding of BI applications and have a “working” system in place, this book will enhance your toolbox. What You Will Learn Install Anaconda, MongoDB, and everything you need to get started with your data analysis Prepare data for analysis by querying cleaning and standardizing data Explore your data by creating a Pandas data frame from MongoDB Gain powerful insights, both statistical and predictive, to make informed business decisions Visualize your data by building dashboards and generating reports Create a complete data processing and business intelligence system In Detail The amount of data produced by businesses and devices is going nowhere but up. In this scenario, the major advantage of Python is that it's a general-purpose language and gives you a lot of flexibility in data structures. Python is an excellent tool for more specialized analysis tasks, and is powered with related libraries to process data streams, to visualize datasets, and to carry out scientific calculations. Using Python for business intelligence (BI) can help you solve tricky problems in one go. Rather than spending day after day scouring Internet forums for “how-to” information, here you'll find more than 60 recipes that take you through the entire process of creating actionable intelligence from your raw data, no matter what shape or form it's in. Within the first 30 minutes of opening this book, you'll learn how to use the latest in Python and NoSQL databases to glean insights from data just waiting to be exploited. We'll begin with a quick-fire introduction to Python for BI and show you what problems Python solves. From there, we move on to working with a predefined data set to extract data as per business requirements, using the Pandas library and MongoDB as our storage engine. Next, we will analyze data and perform transformations for BI with Python. Through this, you will gather insightful data that will help you make informed decisions for your business. The final part of the book will show you the most important task of BI—visualizing data by building stunning dashboards using Matplotlib, PyTables, and iPython Notebook. Style and approach This is a step-by-step guide to help you prepare, explore, analyze and report data, written in a conversational tone to make it easy to grasp. Whether you're new to BI or are looking for a better way to work, you'll find the knowledge and skills here to get your job done efficiently.

Python Data Analysis Cookbook

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Author :
Release : 2016-07-22
Genre : Computers
Kind : eBook
Book Rating : 855/5 ( reviews)

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Book Synopsis Python Data Analysis Cookbook by : Ivan Idris

Download or read book Python Data Analysis Cookbook written by Ivan Idris. This book was released on 2016-07-22. Available in PDF, EPUB and Kindle. Book excerpt: Over 140 practical recipes to help you make sense of your data with ease and build production-ready data apps About This Book Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning Authored by Ivan Idris, expert in python programming and proud author of eight highly reviewed books Who This Book Is For This book teaches Python data analysis at an intermediate level with the goal of transforming you from journeyman to master. Basic Python and data analysis skills and affinity are assumed. What You Will Learn Set up reproducible data analysis Clean and transform data Apply advanced statistical analysis Create attractive data visualizations Web scrape and work with databases, Hadoop, and Spark Analyze images and time series data Mine text and analyze social networks Use machine learning and evaluate the results Take advantage of parallelism and concurrency In Detail Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning. Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You'll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining. In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code. By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios. Style and Approach The book is written in “cookbook” style striving for high realism in data analysis. Through the recipe-based format, you can read each recipe separately as required and immediately apply the knowledge gained.

Python Data Science Cookbook

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Author :
Release : 2015-11-11
Genre : Computers
Kind : eBook
Book Rating : 404/5 ( reviews)

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Book Synopsis Python Data Science Cookbook by : Gopi Subramanian

Download or read book Python Data Science Cookbook written by Gopi Subramanian. This book was released on 2015-11-11. Available in PDF, EPUB and Kindle. Book excerpt: Over 60 practical recipes to help you explore Python and its robust data science capabilitiesAbout This Book• The book is packed with simple and concise Python code examples to effectively demonstrate advanced concepts in action• Explore concepts such as programming, data mining, data analysis, data visualization, and machine learning using Python• Get up to speed on machine learning algorithms with the help of easy-to-follow, insightful recipesWho This Book Is ForThis book is intended for all levels of Data Science professionals, both students and practitioners, starting from novice to experts. Novices can spend their time in the first five chapters getting themselves acquainted with Data Science. Experts can refer to the chapters starting from 6 to understand how advanced techniques are implemented using Python. People from non-Python backgrounds can also effectively use this book, but it would be helpful if you have some prior basic programming experience.What You Will Learn• Explore the complete range of Data Science algorithms• Get to know the tricks used by industry engineers to create the most accurate data science models• Manage and use Python libraries such as numpy, scipy, scikit learn, and matplotlib effectively• Create meaningful features to solve real-world problems• Take a look at Advanced Regression methods for model building and variable selection• Get a thorough understanding of the underlying concepts and implementation of Ensemble methods• Solve real-world problems using a variety of different datasets from numerical and text data modalities• Get accustomed to modern state-of-the art algorithms such as Gradient Boosting, Random Forest, Rotation Forest, and so onIn DetailPython is increasingly becoming the language for data science. It is overtaking R in terms of adoption, it is widely known by many developers, and has a strong set of libraries such as Numpy, Pandas, scikit-learn, Matplotlib, Ipython and Scipy, to support its usage in this field. Data Science is the emerging new hot tech field, which is an amalgamation of different disciplines including statistics, machine learning, and computer science. It's a disruptive technology changing the face of today's business and altering the economy of various verticals including retail, manufacturing, online ventures, and hospitality, to name a few, in a big way.This book will walk you through the various steps, starting from simple to the most complex algorithms available in the Data Science arsenal, to effectively mine data and derive intelligence from it. At every step, we provide simple and efficient Python recipes that will not only show you how to implement these algorithms, but also clarify the underlying concept thoroughly.The book begins by introducing you to using Python for Data Science, followed by working with Python environments. You will then learn how to analyse your data with Python. The book then teaches you the concepts of data mining followed by an extensive coverage of machine learning methods. It introduces you to a number of Python libraries available to help implement machine learning and data mining routines effectively. It also covers the principles of shrinkage, ensemble methods, random forest, rotation forest, and extreme trees, which are a must-have for any successful Data Science Professional.Style and approachThis is a step-by-step recipe-based approach to Data Science algorithms, introducing the math philosophy behind these algorithms.

Machine Learning Cookbook with Python

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Release : 2020-11-12
Genre : Computers
Kind : eBook
Book Rating : 005/5 ( reviews)

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Book Synopsis Machine Learning Cookbook with Python by : Rehan Guha

Download or read book Machine Learning Cookbook with Python written by Rehan Guha. This book was released on 2020-11-12. Available in PDF, EPUB and Kindle. Book excerpt: A Cookbook that will help you implement Machine Learning algorithms and techniques by building real-world projects Ê KEY FEATURESÊ Learn how to handle an entire Machine Learning Pipeline supported with adequate mathematics. Create Predictive Models and choose the right model for various types of Datasets. Learn the art of tuning a model to improve accuracy as per Business requirements. Get familiar with concepts related to Data Analytics with Visualization, Data Science and Machine Learning. DESCRIPTION Machine Learning does not have to be intimidating at all. This book focuses on the concepts of Machine Learning and Data Analytics with mathematical explanations and programming examples. All the codes are written in Python as it is one of the most popular programming languages used for Data Science and Machine Learning. Here I have leveraged multiple libraries like NumPy, Pandas, scikit-learn, etc. to ease our task and not reinvent the wheel. There are five projects in total, each addressing a unique problem. With the recipes in this cookbook, one will learn how to solve Machine Learning problems for real-time data and perform Data Analysis and Analytics, Classification, and beyond. The datasets used are also unique and will help one to think, understand the problem and proceed towards the goal. The book is not saturated with Mathematics, but mostly all the Mathematical concepts are covered for the important topics. Every chapter typically starts with some theory and prerequisites, and then it gradually dives into the implementation of the same concept using Python, keeping a project in the background.Ê Ê WHAT WILL YOU LEARN Understand the working of the O.S.E.M.N. framework in Data Science.Ê Get familiar with the end-to-end implementation of Machine Learning Pipeline. Learn how to implement Machine Learning algorithms and concepts using Python. Learn how to build a Predictive Model for a Business case. WHO THIS BOOK IS FORÊ This cookbook is meant for anybody who is passionate enough to get into the World of Machine Learning and has a preliminary understanding of the Basics of Linear Algebra, Calculus, Probability, and Statistics. This book also serves as a reference guidebook for intermediate Machine Learning practitioners. Ê TABLE OF CONTENTS 1. Boston Crime 2. World Happiness Report 3. Iris Species 4. Credit Card Fraud Detection 5. Heart Disease UCI

Tableau 10 Business Intelligence Cookbook

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Author :
Release : 2016-11-30
Genre : Computers
Kind : eBook
Book Rating : 731/5 ( reviews)

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Book Synopsis Tableau 10 Business Intelligence Cookbook by : Donabel Santos

Download or read book Tableau 10 Business Intelligence Cookbook written by Donabel Santos. This book was released on 2016-11-30. Available in PDF, EPUB and Kindle. Book excerpt: Create powerful, effective visualizations to help analyze your data with Tableau 10 by your side About This Book Cook your favorite Tableau 10 business intelligence recipe with the help of this easy-to-follow book Build beautiful, interactive dashboards and visualizations in Tableau 10 that help you make informed decisions This rich collection of independent recipes cover everything needed to become an advanced Tableau user and get an edge over other Tableau users Who This Book Is For This book is targeted to business, data, and analytics professionals who want to build rich interactive visualizations using Tableau. Familiarity with previous versions of Tableau would be helpful, but is not necessary. What You Will Learn Become familiar with the Tableau interface Build basic to more advanced charts with step-by-step recipes Use filters, calculated fields, parameters, and actions to add interactivity to charts and dashboards Prepare and transform data for analysis using Tableau's built-in tools and functions Create effective and compelling dashboards and story points Leverage Tableau's mapping capabilities to visualize location and shape data Integrate analytics and forecasting to enhance data analysis Get to know tips and tricks to work more quickly and effectively in Tableau Increase your confidence and competence in creating rich, interactive visualizations in Tableau In Detail Tableau is a software tool that can speed up data analysis through its rich visualization capabilities, and help uncover insights for better and smarter decision making. This book is for the business, technology, data and analytics professionals who use and analyze data and data-driven approaches to support business operations and strategic initiatives in their organizations. This book provides easy-to-follow recipes to get the reader up and running with Tableau 10, and covers basic to advanced use cases and scenarios. The book starts with building basic charts in Tableau and moves on to building more complex charts by incorporating different Tableau features and interactivity components. There is an entire chapter dedicated to dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. By the end of this book, you'll have gained confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. Style and approach This book is a collection of independent recipes that cover a wide range of options for data visualization on offer with Tableau. With the help of the recipes in this book, you can explore Tableau and pick the business intelligence solution that's best suited for your needs.

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