Designing Data-Intensive Applications+PYTHON DATA SCIENCE HANDBOOK-COMBO set

Description: DESCRIPTION: ABOUT Python Data Science Handbook: Essential Tools for working with Data by Jake VanderplasFor many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all--IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you'll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithmsABOUT: Designing Data-intensive applications: The Big Ideas Behind Reliable,Scalable and maintainable systems by Martin Kleppmann Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures NOTE: Free fast postage 2-1n-1 combo- Python Data Science Handbook: Essential Tools for working with Data by Jake Vanderplas(paperback)+Designing Data-intensive applications: The Big Ideas Behind Reliable,Scalable and maintainable systems by Martin Kleppmann(paperback). SHIPPING: Books are shipped right away and delivered in 3-4 working days, using FED-EX EXPRESS international shipping service

Price: 50.62 USD

Location: DELHI, DELHI

End Time: 2024-08-19T17:34:53.000Z

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