1.
by
Saitoh, Koki, author.
Call Number
006.31 23
Publication Date
2021
Summary
Discover ways to implement various deep learning algorithms by leveraging Python and other technologies. Deep learning is rapidly becoming the most preferred way of solving data problems. This is thanks, in part, to its huge variety of mathematical algorithms and their ability to find patterns that are otherwise invisible to us. Deep Learning from the Basics begins with a fast-paced introduction to deep learning with Python, its definition, characteristics, and applications. You'll learn how to use the Python interpreter and the script files in your applications, and utilize NumPy and Matplotlib in your deep learning models. As you progress through the book, you'll discover backpropagation--an efficient way to calculate the gradients of weight parameters--and study multilayer perceptrons and their limitations, before, finally, implementing a three-layer neural network and calculating multidimensional arrays. By the end of the book, you'll have the knowledge to apply the relevant technologies in deep learning. What you will learn: Use Python with minimum external sources to implement deep learning programs; Study the various deep learning and neural network theories; Learn how to determine learning coefficients and the initial values of weights; Implement trends such as Batch Normalization, Dropout, and Adam; Explore applications like automatic driving, image generation, and reinforcement learning. Who this book is for: Deep Learning from the Basics is designed for data scientists, data analysts, and developers who want to use deep learning techniques to develop efficient solutions. This book is ideal for those who want a deeper understanding as well as an overview of the technologies. Some working knowledge of Python is a must. Knowledge of NumPy and pandas will be beneficial, but not essential.
Format:
Electronic Resources
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2.3063
by
Cheong, Soon Yau, author.
Call Number
006.37 OCOLC 23ENG20230216
Publication Date
2020
Summary
This book is a step-by-step guide to show you how to implement generative models in TensorFlow 2.x from scratch. You'll get to grips with the image generative technology by covering autoencoders, style transfer, and GANs as well as fundamental and state-of-the-art models.
Format:
Electronic Resources
Relevance:
1.9791
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by
Saleh, Hyatt.
Call Number
006.31 23
Publication Date
2020
Summary
With this hands-on, self-paced guide, you'll explore crucial deep learning topics and discover the structure and syntax of PyTorch. Challenging activities and interactive exercises will keep you motivated and encourage you to build intelligent applications effectively.
Format:
Electronic Resources
Relevance:
1.9361
by
Buelta, Jaime, author.
Call Number
005.133 23
Publication Date
2020
Summary
This new and updated edition includes 75 recipes that cover the entire spectrum of skills you need for enterprise process automation and save time wasted in performing recurrent tasks. This book also features three new chapters that focus on using Python for automating testing routines, machine learning projects, and for working with messy ...
Format:
Electronic Resources
Relevance:
1.6444
by
Okasha, Karim.
Call Number
005.43 23
Publication Date
2020
Summary
This book includes over 100 actionable recipes to supercharge Ansible and automate network devices from different vendors and build networking solutions across cloud providers like AWS, GCP, and Azure. You will be able to effectively manage your network infrastructure in various environments using Ansible - be it a datacenter, or a service ...
Format:
Electronic Resources
Relevance:
1.5325
by
Phillips, Dusty.
Call Number
005.117 22
Publication Date
2010
Summary
Annotation Object Oriented Programming is a very important aspect of modern programming languages. The basic principles of Object Oriented Programming are relatively easy to learn. Putting them together into working designs can be challenging.<br /><br />This book makes programming more of a pleasure than a chore using powerful Python 3 object-oriented features of Python 3. It clearly demonstrates the core OOP principles and how to correctly implement OOP in Python.<br /><br />Object Oriented Programming ranks high in importance among the many models Python supports. Yet, many programmers never bother learning the powerful features that make this language object oriented.<br /><br />The book teaches when and how OOP should be correctly applied. It emphasizes not only the simple syntax of OOP in Python, but also how to combine these objects into well-designed software.<br /><br />This book will introduce you to the terminology of the object-oriented paradigm, focusing on object-oriented design with step-by-step examples. It will take you from simple inheritance, one of the most useful tools in the object-oriented programmer's toolbox, all the way through to cooperative inheritance, one of the most complicated. You will be able to raise, handle, define, and manipulate exceptions.<br /><br />You will be able to integrate the object-oriented and the not-so-object-oriented aspects of Python. You will also be able to create maintainable applications by studying higher level design patterns. You'll learn the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems will be introduced to you. You'll understand the joy of unit testing and just how easy they are to create. You'll even study higher level libraries such as database connectors and GUI toolkits and how they apply object-oriented principles.<br /><br />Harness the power of Python 3 objects; it's not just a scripting language.
Format:
Electronic Resources
Relevance:
0.3428
by
Harbour, Jonathan S. (Jonathan S. Harbour).
Call Number
005.133 23
Publication Date
2011
Format:
Electronic Resources
Relevance:
0.3315
by
Pimpler, Eric.
Call Number
006.76
Publication Date
2013
Summary
This book is written in a helpful, practical style with numerous hands-on recipes and chapters to help you save time and effort by using Python to power ArcGIS to create shortcuts, scripts, tools, and customizations.""Programming ArcGIS 10.1 with Python Cookbook"" is written for GIS professionals who wish to revolutionize their ArcGIS workflow with Python. Basic Python or programming knowledge is essential.
Format:
Electronic Resources
Relevance:
0.3169
by
Romano, Fabrizio, author.
Call Number
005.133 23ENG20230201
Publication Date
2021
Summary
Get up and running with Python through concise tutorials and practical projects in this fully updated edition Key Features Discover how to think like a Python programmer Extensively revised with richer examples, Python 3.9 syntax, and new chapters on APIs and packaging and distributing Python code Learn the fundamentals of Python through real-world projects in API development, GUI programming, and data science Book Description Learn Python Programming, Third Edition is both a theoretical and practical introduction to Python, an extremely flexible and powerful programming language that can be applied to many disciplines. This book will make learning Python easy and give you a thorough understanding of the language. You'll learn how to write programs, build modern APIs, and work with data by using renowned Python data science libraries. This revised edition covers the latest updates on API management, packaging applications, and testing. There is also broader coverage of context managers and an updated data science chapter. The book empowers you to take ownership of writing your software and become independent in fetching the resources you need. You will have a clear idea of where to go and how to build on what you have learned from the book. Through examples, the book explores a wide range of applications and concludes by building real-world Python projects based on the concepts you have learned. What you will learn Get Python up and running on Windows, Mac, and Linux Write elegant, reusable, and efficient code in any situation Avoid common pitfalls like duplication, complicated design, and over-engineering Understand when to use the functional or object-oriented approach to programming Build a simple API with FastAPI and program GUI applications with Tkinter Get an initial overview of more complex topics such as data persistence and cryptography Fetch, clean, and manipulate data, making efficient use of Python's built-in data structures Who this book is for This book is for anyone who has some programming experience, but not necessarily with Python. Some knowledge of basic programming concepts will come in handy, although it is not a requirement.
Format:
Electronic Resources
Relevance:
0.3038
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