The Python Workbook: A Brief Introduction with Exercises and Solutions, Stephenson Ben
Автор: Guido Sarah Название: Introduction to Machine Learning with Python ISBN: 1449369413 ISBN-13(EAN): 9781449369415 Издательство: Wiley Рейтинг: Цена: 63350.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.
Автор: Fehr Hans Название: Introduction to Computational Economics Using Fortran ISBN: 0198850379 ISBN-13(EAN): 9780198850373 Издательство: Oxford Academ Рейтинг: Цена: 46980.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This exercise and solutions manual accompanies the main edition of Introduction to Computational Economics Using Fortran. It enables students of all levels to practice the skills and knowledge needed to conduct economic research using Fortran.
Zed Shaw has crafted the perfect course for the beginning C programmer eager to advance their skills in any language. Follow it and you will learn the many skills early and junior programmers need to succeed-just like the hundreds of thousands of programmers Zed has taught to date You bring discipline, commitment, persistence, and experience with any programming language; the author supplies everything else. In Learn C the Hard Way, you'll learn C by working through 52 brilliantly crafted exercises. Watch Zed Shaw's teaching video and read the exercise. Type his code precisely. (No copying and pasting ) Fix your mistakes. Watch the programs run. As you do, you'll learn what good, modern C programs look like; how to think more effectively about code; and how to find and fix mistakes far more efficiently. Most importantly, you'll master rigorous defensive programming techniques, so you can use any language to create software that protects itself from malicious activity and defects. Through practical projects you'll apply what you learn to build confidence in your new skills. Shaw teaches the key skills you need to start writing excellent C software, including
Setting up a C environment
Basic syntax and idioms
Compilation, make files, and linkers
Operators, variables, and data types
Program control
Arrays and strings
Functions, pointers, and structs
Memory allocation
I/O and files
Libraries
Data structures, including linked lists, sort, and search
Stacks and queues
Debugging, defensive coding, and automated testing
Fixing stack overflows, illegal memory access, and more
Breaking and hacking your own C code
It'll Be Hard at First. But Soon, You'll Just Get It-And That Will Feel Great This tutorial will reward you for every minute you put into it. Soon, you'll know one of the world's most powerful programming languages. You'll be a C programmer. Watch Zed, too The accompanying DVD contains 5+ hours of passionate, powerful teaching: a complete C video course If you purchase the digital edition, be sure to read "Where Are the Companion Content Files" at the end of the eBook to learn how to access the videos.
Автор: Stephenson, Ben Название: Python workbook ISBN: 3030188728 ISBN-13(EAN): 9783030188726 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
While other textbooks devote their pages to explaining introductory programming concepts, The Python Workbook focuses exclusively on exercises, following the philosophy that computer programming is a skill best learned through experience and practice.
Designed to support and encourage hands-on learning about programming, this student-friendly work contains 174 exercises, spanning a variety of academic disciplines and everyday situations. Solutions to selected exercises are also provided, supported by brief annotations that explain the technique used to solve the problem, or highlight specific points of Python syntax. No background knowledge is required to solve the exercises, beyond the material covered in a typical introductory Python programming course.
Features: uses an accessible writing style and easy-to-follow structure; includes a mixture of classic exercises from the fields of computer science and mathematics, along with exercises that connect to other academic disciplines; presents the solutions to approximately half of the exercises; provides annotations alongside the solutions, which explain the approach taken to solve the problem and relevant aspects of Python syntax; offers a variety of exercises of different lengths and difficulties; contains exercises that help the development of programming skills using if statements, loops, basic functions, lists, dictionaries, files, and recursive functions.
Undergraduate students undergoing their first programming course and wishing to enhance their programming abilities will find the exercises and solutions provided in this book to be ideal for their needs.
Автор: Vaughan, Lee Название: Python tools for scientists ISBN: 1718502664 ISBN-13(EAN): 9781718502666 Издательство: Random House (USA) Рейтинг: Цена: 30650.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Doing Science With Python introduces readers to the most popular coding tools for scientific research, such as Anaconda, Spyder, Jupyter Notebooks, and JupyterLab, as well as dozens of important Python libraries for working with data, including NumPy, matplotlib, and pandas. No prior programming experience is required! You'll be guided through setting up a professional coding environment, then get a crash course on programming with Python, and explore the many tools and libraries ideal for working with data, designing visualisations, simulating natural events, and more.
Автор: Sandeep Nagar Название: Introduction to Python for Engineers and Scientists ISBN: 1484232038 ISBN-13(EAN): 9781484232033 Издательство: Springer Рейтинг: Цена: 26080.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.
In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you'll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts.
What You'll Learn
Understand the fundamentals of the Python programming language
Apply Python to numerical computational programming projects in engineering and science
Discover the Pythonic way of life
Apply data types, operators, and arrays
Carry out plotting for visualization
Work with functions and loops
Who This Book Is For
Engineers, scientists, researchers, and students who are new to Python. Some prior programming experience would be helpful but not required.
Do you Want to learn more about Python Programming, Machine Learning and Artificial Intelligence ?.... then read on.
Python is a powerful programming language that can be used for the development of various types of applications. It is an Object-Oriented Programming language and it is interpreted rather than being compiled.
Python is considered to be among the most beloved programming languages in any circle of programmers. Software engineers, hackers, and Data Scientists alike are in love with the versatility that Python has to offer. Besides, the Object-Oriented feature of Python coupled with its flexibility is also some of the major attractions for this language. Programmers are now developing a wide range of mobile as well as web applications that we enjoy on an everyday basis.
Python Programming Crash Course doesn't make any assumptions about your background or knowledge of Python or computer programming. You need no prior knowledge to benefit from this book. You will be guided step by step using a logical and systematic approach. As new concepts, commands, or jargon are encountered they are explained in plain language, making it easy for anyone to understand.
In this Book you will learning:
Introduction ito iPython
Variables
Operators
Loops
Functions
Object-Oriented iProgramming-OOP
Modules
File ihandling
Would you like to know more?
Download the Book, Python Programming Crash Course .Scroll to the top of the page and click the "Buy now" button to get your copy now.
Автор: Academy Computer Programming Название: Python: This Book Includes: Programming, Machine Learning and Data Science. An Hands-On Introduction to Python Programming Lan ISBN: 1914185161 ISBN-13(EAN): 9781914185168 Издательство: Неизвестно Рейтинг: Цена: 26620.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Have you always wanted to learn computer programming but you're worried it will take too long? Would you like to automate something simple with your PC but you don't know how to do it? Or maybe you know other programming languages and are interested in learning Python quickly?
As a beginner you might think that programming is difficult and the possibility to give up before mastering it could be high... So, if you have a project to develop you could think on hiring a programmer to shorten the time. This may seem like a good idea but it is certainly very expensive. Otherwise you could waste your time pursuing tutorials online.
The best solution is to follow a complete programming manual with hands-on projects and practical exercises.
What you will find inside and a quick overview of the main topics:
✓ Why Python is considered the best programming language for a beginner
✓ The most common mistakes to avoid when you start programming
✓ BOOK 1: PYTHON PROGRAMMING
- The 7 built-in functions to make your life easier while coding a software program
- The program you need to develop your first own application
✓ BOOK 2: PYTHON MACHINE LEARNING
- The algorithms that will make your life easier
- The 2 libraries you need implementing to develop the desired ML models
✓ BOOK 3: PYTHON DATA SCIENCE
- 3 actions required to gain insights from big data
- A simple method to implement predictive analytics
✓ Some projects to write Python codes in less than a week
✓ Quizzes at the end of every chapter to review immediately what you've learned
Why is this book different?
Computer Programming Academy structured these guides as a course with seven chapters for seven days with special exercises for each section.This protocol, tested on both beginners and people who were already familiar with coding, takes advantage of the principle of diving, concentrating learning in one week. The result? The content of the course was learned faster and remembered longer.
Even if you're completely new to programming in 2020 or you are just looking to widen your skills as programmer this book is perfect for you.
Now's the best time to begin learning Python... click the "BUY NOW" button and get started
Inside this book you will find all the basic notions to start with Python and all the programming concepts to build machine learning models. With our proven strategies you will write efficient Python codes in less than a week!
Автор: Korstanje, Joos Название: Machine learning on geographical data using python ISBN: 1484282868 ISBN-13(EAN): 9781484282861 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Get up and running with the basics of geographic information systems (GIS), geospatial analysis, and machine learning on spatial data in Python. This book starts with an introduction to geodata and covers topics such as GIS and common tools, standard formats of geographical data, and an overview of Python tools for geodata. Specifics and difficulties one may encounter when using geographical data are discussed: from coordinate systems and map projections to different geodata formats and types such as points, lines, polygons, and rasters. Analytics operations typically applied to geodata are explained such as clipping, intersecting, buffering, merging, dissolving, and erasing, with implementations in Python. Use cases and examples are included. The book also focuses on applying more advanced machine learning approaches to geographical data and presents interpolation, classification, regression, and clustering via examples and use cases. This book is your go-to resource for machine learning on geodata. It presents the basics of working with spatial data and advanced applications. Examples are presented using code (accessible at github.com/Apress/machine-learning-geographic-data-python) and facilitate learning by application. What You Will Learn * Understand the fundamental concepts of working with geodata * Work with multiple geographical data types and file formats in Python * Create maps in Python * Apply machine learning on geographical data Who This Book Is For Readers with a basic understanding of machine learning who wish to extend their skill set to analysis of and machine learning on spatial data while remaining in a common data science Python environment
Автор: Nikhil Ketkar Название: Deep Learning with Python ISBN: 1484227654 ISBN-13(EAN): 9781484227657 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Chapter 1: An intuitive look at the fundamentals of deep learning based on practical applicationsChapter 2: A survey of the current state-of-the-art implementations of libraries, tools and packages for deep learning and the case for the Python ecosystemChapter 3: A detailed look at Keras [1], which is a high level framework for deep learning suitable for beginners to understand and experiment with deep learningChapter 4: A detailed look at Theano [2], which is a low level framework for implementing architectures and algorithms in deep learning from scratchChapter 5: A detailed look at Caffe [3], which is highly optimized framework for implementing some of the most popular deep learning architectures (mainly computer vision)Chapter 6: A brief introduction to GPUs and why they are a game changer for Deep LearningChapter 7: A brief introduction to Automatic DifferentiationChapter 8: A brief introduction to Backpropagation and Stochastic Gradient DescentChapter 9: A survey of Deep Learning ArchitecturesChapter 10: Advice on running large scale experiments in deep learning and taking models to productionChapter 11: Introduction to TensorflowChapter 12: Introduction to PyTorchChapter 13: Regularization TechniquesChapter 14: Training Deep Leaning Models
Python is a general-purpose high level programming language that is being increasingly used in data science and in designing machine learning algorithms. This book provides a quick introduction to Python and its libraries like numpy, scipy, pandas, matplotlib and explains how it can be applied to develop machine learning algorithms that solve real world problems. This book starts with an introduction to machine learning with Python language and shows you how to setup Python and its packages. It further covers all important concepts such as exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation.
This tutorial also provides various projects that teaches you the techniques and functionalities such as news topic classification, spam email detection, online ad click-through prediction, stock prices forecast and other several important machine learning algorithms.
This tutorial has been prepared for professionals aspiring to learn machine learning with python and develop applications involving machine learning techniques such as recommendation, classification, and clustering. Through this tutorial, you will learn to solve data-driven problems and implement your solutions using the powerful yet simple programming language, Python and its packages. After completing this tutorial, you will gain a broad picture of the machine learning environment and the best practices and techniques for machine learning algorithms in python .
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