Автор: Mele, Antonio Belderbos, Bob Название: Django 4 by example ISBN: 1801813051 ISBN-13(EAN): 9781801813051 Издательство: Неизвестно Рейтинг: Цена: 10918.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Django 4 by Example is the fourth edition of the best-selling franchise that helps you build web applications. This book will guide you through the entire process of developing professional web applications with Django. The book focuses on explaining how the Django Web Framework works by building multiple projects from the ground up.
Название: Python Programming on Win32 ISBN: 1565926218 ISBN-13(EAN): 9781565926219 Издательство: Wiley Рейтинг: Цена: 7602.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Demonstrates how to use Python as a serious Windows development tool. The book addresses all the basic technolgies for common integration tasks on Windows, explaining both the Windows issues and the Python code needed to glue things together.
Автор: Langtangen Hans Petter Название: A Primer on Scientific Programming with Python ISBN: 3662498863 ISBN-13(EAN): 9783662498866 Издательство: Springer Рейтинг: Цена: 4890.00 р. 6986.00-30% Наличие на складе: Есть (1 шт.) Описание: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches 'Matlab-style' and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.From the reviews: Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. … Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science.Alex Small, IEEE, CiSE Vol. 14 (2), March?/April 2012 “This fourth edition is awonderful, inclusive textbook that covers pretty much everything one needs toknow to go from zero to fairly sophisticated scientific programming in Python…”Joan Horvath, Computing Reviews, March2015
Автор: Yogendra Narayan Pandey et al Название: Machine learning in the oil and gas industry ISBN: 1484260937 ISBN-13(EAN): 9781484260937 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches.
The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering.
Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will LearnUnderstanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industryGet the basic concepts of computer programming and machine and deep learning required for implementing the algorithms usedStudy interesting industry problems that are good candidates for being solved by machine and deep learningDiscover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.
Название: Python for MBAs ISBN: 0231193920 ISBN-13(EAN): 9780231193924 Издательство: Wiley Рейтинг: Цена: 18533.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is an introduction to programming with Python for MBA students and others in business positions who need a crash course. Beginning with fundamentals such as variables, strings, lists, and functions, it builds up to data analytics and practical ways to derive value from large and complex datasets.
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What is Data Science?
The Python Coding Language
Some of the Basic Coding in Python
The Best Python Libraries to Use with Data Science
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Working with Anaconda in Python
The Basics of the Pandas Library
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There are hundreds of different programming languages out there in the world, with Wikipedia listing over 700 notable languages. Given how many languages you could potentially learn, why learn Python?
Python is one of the most popular programming languages in the word in 2020 and specially for data science. Every day people use it to do cool things like Automation, they use it in Artificial Intelligence, as well as Building Applications and Websites like Instagram and Dropbox. YouTube, Pinterest, and SurveyMonkey are all built on Python. So if you are looking for a trendy job, like data scientist, Python is for you.
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Python can be used on a wide variety of operating systems, and its clean, readable code style makes it relatively beginner-friendly. While not as fast as other languages, such as C++ or JAVA, Python code is often much shorter and simpler than other languages.
Python has seen an explosion in popularity in recent years, driven by several aspects that make it an incredibly versatile and intuitive language. A huge selling point of Python is the cleanliness and readability of its syntax and structure. Commands in Python can often be carried out using simple English keywords, which makes the language much more intuitive than many other languages. Python is also quite versatile in the sense that it supports both structured programming and object-oriented programming approaches. Python even allows the use of certain aspects of functional programming.
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This book covers:
The world of data science technologies
Customer targeting and segmentation
Application of machine learning
Data scientist: the sexiest job in the 21st century
Learning Python from scratch
What is Python
Why learn Python
Projects on Python
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Despite its simplicity, Python is also sturdy and robust enough to carry out complex scientific and mathematical tasks. Python has been designed with features that drastically simplify the visualization and analysis of data, and Python is also the go-to choice for the creation of machine learning models and artificial intelligence.
Be it machine learning, data analytics, data processing, web development, enterprise software development or taking the photo of Blackhole: Python is everywhere. Beloved by the data scientists and new generation developers, Pyhton will eat the word
Описание: Python for Data Science: The Best Crash Course Guide for Beginners Ever
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Data analysis plays an important role in many aspects of life today. From the moment you wake up, you interact with data at different levels. A lot of important decisions are made based on data analytics. Companies need data to help them meet many of their goals. As the population of the world keeps growing, its customer base keeps expanding. In light of this, they must find ways of keeping their customers happy while at the same time meeting their business goals.
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This book covers:
- What is Data Analysis
- Python Crash Course
- Data Munging
- Why Data Preprocessing Is Important
- What is Data Wrangling?
- Inheritances to Clean Up the Code
- The Different Types of Data We Can Work With
- The Importance of Data Visualization
- Indexing and selecting arrays
- Common Debugging Tools
- Neural Network and What to Use for?
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Автор: Oliver Deborah Название: Python for data analysis ISBN: 1801256519 ISBN-13(EAN): 9781801256513 Издательство: Неизвестно Рейтинг: Цена: 2759.00 р. Наличие на складе: Нет в наличии.
Описание:
This audiobook offers a smart introduction to data analysis using Python and is one of the best books available in the market. It covers basic and advanced data analysis concepts in detail using several Python libraries that are well-known for their data analytical features. The book explains everything in detail and, sometimes, enhances the listeners' knowledge by touching on some advanced topics that need strict adherence and sincerity to master.
In this audiobook, we start with an introduction to data analysis using the catering system as an example. We always strive to give Python code for the concepts discussed because it gives a practical understanding of the topic.
Below are some the most important topics we have discussed in this book, in no particular order:
Data analysis with a universal catering system that helps us understand different data mining models available
Introduction to Python, Numpy, and Pandas and their installation
Numpy and advanced array functions it offers
Pandas and functions it offers
Basic and advanced data analysis skills
Plotting features in data analysis
Time series functions in data analysis
E-commerce example to understand the real-world application of data analysis
So, what are you waiting for? Go on a drive to conquer data analysis skills by using this book.
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