Learning Data Mining with Python: Use Python to manipulate data and build predictive models, 2nd Edition - Softcover
Synopsis
Quickly learn and employ practical recipes for developing real-world, cross-platform applications using Delphi.
Key Features
- Get to grips with Delphi to build and deploy various cross-platform applications
- Design and deploy real-world apps by implementing a single source codebase
- Build robust and optimized GUI applications with ease
Book Description
Delphi is a cross-platform integrated development environment (IDE) that supports rapid application development on different platforms, saving you the pain of wandering amid GUI widget details or having to tackle inter-platform incompatibilities.
Delphi Cookbook begins with the basics of Delphi and gets you acquainted with JSON format strings, XSLT transformations, Unicode encodings, and various types of streams. You'll then move on to more advanced topics such as developing higher-order functions and using enumerators and run-time type information (RTTI). As you make your way through the chapters, you'll understand Delphi RTL functions, use FireMonkey in a VCL application, and cover topics such as multithreading, using aparallel programming library and deploying Delphi on a server. You'll take a look at the new feature of WebBroker Apache modules, join the mobile revolution with FireMonkey, and learn to build data-driven mobile user interfaces using the FireDAC database access framework. This book will also show you how to integrate your apps with Internet of Things (IoT).
By the end of the book, you will have become proficient in Delphi by exploring its different aspects such as building cross-platforms and mobile applications, designing server-side programs, and integrating these programs with IoT.
What you will learn
- Develop visually stunning applications using FireMonkey
- Deploy LiveBinding effectively with the right object-oriented programming (OOP) approach
- Create RESTful web services that run on Linux or Windows
- Build mobile apps that read data from a remote server efficiently
- Call platform native API on Android and iOS for an unpublished API
- Manage software customization by making better use of an extended RTTI
- Integrate your application with IOT
Who this book is for
Delphi Cookbook is for intermediate developers with a basic knowledge of Delphi who want to discover and understand all the development possibilities offered by it.
"synopsis" may belong to another edition of this title.
About the Author
Robert Layton
Robert Layton is a data scientist investigating data-driven applications to businesses across a number of sectors. He received a PhD investigating cybercrime analytics from the Internet Commerce Security Laboratory at Federation University Australia, before moving into industry, starting his own data analytics company dataPipeline. Next, he created Eureaktive, which works with tech-based startups on developing their proof-of-concepts and early-stage prototypes. Robert also runs the LearningTensorFlow website, which is one of the world's premier tutorial websites for Google's TensorFlow library. Robert is an active member of the Python community, having used Python for more than 8 years. He has presented at PyConAU for the last four years and works with Python Charmers to provide Python-based training for businesses and professionals from a wide range of organisations. Robert can be best reached via Twitter @robertlayton
"About this title" may belong to another edition of this title.
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Learning Data Mining with Python - Second Edition: Use Python to manipulate data and build predictive models
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Learning Data Mining with Python - Second Edition
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Digital. Condition: New. Harness the power of Python to develop data mining applications, analyze data, delve into machine learning, explore object detection using Deep Neural Networks, and create insightful predictive models.About This Book. Use a wide variety of Python libraries for practical data mining purposes. Learn how to find, manipulate, analyze, and visualize data using Python. Step-by-step instructions on data mining techniques with Python that have real-world applications.Who This Book Is ForIf you are a Python programmer who wants to get started with data mining, then this book is for you. If you are a data analyst who wants to leverage the power of Python to perform data mining efficiently, this book will also help you. No previous experience with data mining is expected.What You Will Learn. Apply data mining concepts to real-world problems. Predict the outcome of sports matches based on past results. Determine the author of a document based on their writing style. Use APIs to download datasets from social media and other online services. Find and extract good features from difficult datasets. Create models that solve real-world problems. Design and develop data mining applications using a variety of datasets. Perform object detection in images using Deep Neural Networks. Find meaningful insights from your data through intuitive visualizations. Compute on big data, including real-time data from the internetIn DetailThis book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK.You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now.With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.Style and approachThis book will be your comprehensive guide to learning the various data mining techniques and implementing them in Python. A variety of real-world datasets is used to explain data mining techniques in a very crisp and easy to understand manner. Seller Inventory # LU-9781787126787
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