Learning Python
Learning Python

Author: Mark Lutz

Publisher: "O'Reilly Media, Inc."

Published: 2013-06-12

Total Pages: 1740

ISBN-13: 1449355692

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Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code. Explore Python’s major built-in object types such as numbers, lists, and dictionaries Create and process objects with Python statements, and learn Python’s general syntax model Use functions to avoid code redundancy and package code for reuse Organize statements, functions, and other tools into larger components with modules Dive into classes: Python’s object-oriented programming tool for structuring code Write large programs with Python’s exception-handling model and development tools Learn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing

Federal Depository Library Directory
Federal Depository Library Directory

Author:

Publisher:

Published: 2000

Total Pages: 384

ISBN-13:

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This is the official GPO directory information (names, addresses, telephone numbers, etc.) of all federal depository libraries. The electronic version is created from the PROFILE portion of the LPS PAMALA database. The results screens include links to each library's latest Item Lister item selection profile record, and, as applicable, a hotlinked email address and a Depository Web site URL. This database is updated on the first Friday of the month.

Developing Technical Training
Developing Technical Training

Author: Ruth C. Clark

Publisher: John Wiley & Sons

Published: 2011-01-11

Total Pages: 288

ISBN-13: 1118047419

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Since it was first published almost twenty years ago, Developing Technical Training has been a reliable resource for both new and seasoned training specialists. The third edition of this classic book outlines a systematic approach called the Instructional Systems Design (ISD) process that shows how to teach technical content defined as facts, concepts, processes, procedures, and principles. Whether you teach “hard” or “soft” skills, or design lessons for workbooks or computers, you will find the best training methods in this book. Using these techniques, you can create learning environments that will lead to the most efficient and effective acquisition of new knowledge and skills. Throughout the book, Clark defines each content type and illustrates how to implement the best instructional methods for delivery in either print or e-learning media.

Deep Learning for Coders with fastai and PyTorch
Deep Learning for Coders with fastai and PyTorch

Author: Jeremy Howard

Publisher: O'Reilly Media

Published: 2020-06-29

Total Pages: 624

ISBN-13: 1492045497

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Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala