Search results for "Python in Depth"
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Real World Instrumentation with Python
With this convenient, single-source reference, you'll learn how to develop instrumentation software with Python that lets you monitor or control devices in the physical world. Whether you need to acquire data from a hardware device or automate its functions, this book shows you how to build interfaces that include everything from software to wiring. You get step-by-step instructions, clear examples, and hands-on tips and hints for interfacing a PC to the real world, along with advice to help you avoid common pitfalls. Use the book's hardware survey to discover the interface type for your particular device, and then follow detailed examples to develop the interface with Python and C. Organized by interface type, data processing activities, and user interface implementations, this book is for anyone who works with instrumentation, robotics, data acquisition, or process control.* Understand how to define the scope of an application and determine the algorithms necessary -- and why it's important * Learn how to use industry-standard interfaces such as RS-232, RS-485, and GPIB * Create low-level extension modules in C to interface Python with a variety of hardware and test instruments * Explore the console, curses, TkInter, and wxPython for graphical and text-based user interfaces * Use open source software tools and libraries to reduce cost and avoid implementing functionality from scratch
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Hands-on Time Series Analysis with Python
Learn the concepts of time series from traditional to bleeding-edge techniques. This book uses comprehensive examples to clearly illustrate statistical approaches and methods of analyzing time series data and its utilization in the real world. All the code is available in Jupyter notebooks.You'll begin by reviewing time series fundamentals, the structure of time series data, pre-processing, and how to craft the features through data wrangling. Next, you'll look at traditional time series techniques like ARMA, SARIMAX, VAR, and VARMA using trending framework like StatsModels and pmdarima. The book also explains building classification models using sktime, and covers advanced deep learning-based techniques like ANN, CNN, RNN, LSTM, GRU and Autoencoder to solve time series problem using Tensorflow. It concludes by explaining the popular framework fbprophet for modeling time series analysis. After reading Hands -On Time Series Analysis with Python, you'll be able to apply these new techniques in industries, such as oil and gas, robotics, manufacturing, government, banking, retail, healthcare, and more. What You'll Learn:· Explains basics to advanced concepts of time series· How to design, develop, train, and validate time-series methodologies· What are smoothing, ARMA, ARIMA, SARIMA,SRIMAX, VAR, VARMA techniques in time series and how to optimally tune parameters to yield best results· Learn how to leverage bleeding-edge techniques such as ANN, CNN, RNN, LSTM, GRU, Autoencoder to solve both Univariate and multivariate problems by using two types of data preparation methods for time series.· Univariate and multivariate problem solving using fbprophet. Who This Book Is ForData scientists, data analysts, financial analysts, and stock market researchers
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Artificial Intelligence with Python
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more.Key FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook DescriptionArtificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications.This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data.Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques.What you will learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is forThe intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.
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Python Continuous Integration and Delivery
Gain the techniques and tools that enable a smooth and efficient software development process in this quick and practical guide on Python continuous integration (CI) and continuous delivery (CD). Based on example applications, this book introduces various kinds of testing and shows you how to set up automated systems that run these tests, and install applications in different environments in controlled ways. Python Continuous Integration and Delivery tackles the technical problems related to software development that are typically glossed over in pure programming texts.After reading this book, you’ll see that in today's fast-moving world, no software project can afford to go through development, then an integration phase of unpredictable length and complexity, and finally be shipped to the customer -- just to find out that the resulting application didn't quite fill their need. Instead, you’ll discover that practicing continuous integration and continuous delivery reduces the risks by keeping changes small and automating otherwise painful processes. What You Will LearnCarry out various kinds of testing, including unit testing and continuous integration testing, of your Python code using JenkinsBuild packages and manage repositoriesIncorporate Ansible and Go for automated packaging and other deploymentsManage more complex and robust deploymentsWho This Book Is ForPython programmers and operating staff that work with Python applications.
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Python Programming
Maintaining a practical perspective, Python Programming: A Practical Approach acquaints you with the wonderful world of programming. The book is a starting point for those who want to learn Python programming. The backbone of any programming, which is the data structure and components such as strings, lists, etc., have been illustrated with many examples and enough practice problems to instill a level of self-confidence in the reader.Drawing on knowledge gained directly from teaching Computer Science as a subject and working on a wide range of projects related to ML, AI, deep learning, and blockchain, the authors have tried their best to present the necessary skills for a Python programmer. Once the foundation of Python programming is built and the readers are aware of the exact structure, dimensions, processing, building blocks, and representation of data, they can readily take up their specific problems from the area of interest and solve them with the help of Python. These include, but are not limited to, operators, control flow, strings, functions, module processing, object-oriented programming, exception and file handling, multithreading, synchronization, regular expressions, and Python database programming.This book on Python programming is specially designed to keep readers busy with learning fundamentals and generates a sense of confidence by attempting the assignment problems. We firmly believe that explaining any particular technology deviates from learning the fundamentals of a programming language. This book is focused on helping readers attempt implementation in their areas of interest through the skills imparted through this book. We have attempted to present the real essence of Python programming, which you can confidently apply in real life by using Python as a tool.Salient Features Based on real-world requirements and solution. Simple presentation without avoiding necessary details of the topic. Executable programs on almost every topic. Plenty of exercise questions, designed to test readers’ skills and understanding.Purposefully designed to be instantly applicable, Python Programming: A Practical Approach provides implementation examples so that the described subject matter can be immediately implemented due to the well-known versatility of Python in handling different data types with ease.
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Beginning ChatGPT for Python
Unlock the future of software development and empower yourself to elevate your Python applications by harnessing the power of AI as this field continues to grow and evolve. Perfect for beginner to intermediate Python programmers, this book breaks down the essentials of using ChatGPT and OpenAI APIs.You'll start with the basics, learning to authenticate, send prompts, generate responses, test in the Playground, and handle errors with ease. Each chapter includes hands-on exercises that bring concepts to life, demonstrating different API functionalities and practical applications. You'll master models like GPT-4o, GPT-4, GPT-3.5, Whisper, and DALL-E, enabling you to enhance your applications with cutting-edge AI.Discover how generative AI tools like ChatGPT can automate tedious tasks rather than replace jobs. Leverage ChatGPT’s powerful Natural Language Processing (NLP) capabilities to handle various formats of unstructured text within your Python apps. Quickly see how easy it is to use ChatGPT as your AI-pair programmer, boosting your productivity and speed.This step-by-step guide will have you creating intelligent chatbots that can automatically process messages from Slack or Discord. With Beginning ChatGPT for Python, you'll master the ChatGPT and OpenAI APIs, building intelligent applications that offer a personalized and engaging user experience.What You’ll LearnConnect with the ChatGPT and OpenAI APIs and send effective prompts.Harness parameters like temperature and topp to create unique and engaging responses from ChatGPT.Create an intelligent assistant bot for Slack that automates tasks and enhances productivity.Develop a bot that can moderate conversations and manage communities on Discord.Add context to your prompts to get more accurate and relevant responses. Who This Book Is For Python developers and enthusiasts who aspire to employ OpenAI and ChatGPT in the creation of intelligent applications to enhance productivity.
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3D Deep Learning with Python
Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with easeKey FeaturesUnderstand 3D data processing with rendering, PyTorch optimization, and heterogeneous batchingImplement differentiable rendering concepts with practical examplesDiscover how you can ease your work with the latest 3D deep learning techniques using PyTorch3DBook DescriptionWith this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time.Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You’ll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you’ll realize how coding for these deep learning models becomes easier using the PyTorch3D library.By the end of this deep learning book, you’ll be ready to implement your own 3D deep learning models confidently.What you will learnDevelop 3D computer vision models for interacting with the environmentGet to grips with 3D data handling with point clouds, meshes, ply, and obj file formatWork with 3D geometry, camera models, and coordination and convert between themUnderstand concepts of rendering, shading, and more with easeImplement differential rendering for many 3D deep learning modelsAdvanced state-of-the-art 3D deep learning models like Nerf, synsin, mesh RCNNWho this book is forThis book is for beginner to intermediate-level machine learning practitioners, data scientists, ML engineers, and DL engineers who are looking to become well-versed with computer vision techniques using 3D data.
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Introduction to Programming for Researchers
Enhance your computational and programming skills using Bash and Python to improve productivity and efficiency in research projects. This book is an essential guide for STEM researchers. Structured into several parts, each builds on the previous ones to ensure a solid foundation in programming. You'll begin with the basics of digital computation and operating systems, then write pipelines and scripts in Bash, focusing on tools for working with datasets in text files. After introducing algorithms and floating-point numbers, the book transitions to Python, emphasizing SciPy libraries and built-in features like type hints and f-strings. IPython and Jupyter notebooks are integrated into the lessons throughout. Programming best practices are taught, alongside programming basics. These include documentation and unit testing. As the target audience is STEM students and professionals, examples make heavy use of datasets and the SciPy software stack, especially NumPy, Matplotlib, Pandas, and SymPy. Introduction to Programming for Researchers will foster a deeper understanding of computational tools and critical programming skills, empowering you to tackle complex datasets and enhance their research capabilities. What You Will Learn Apply programming skills to enhance research productivity and efficiency. Write Bash pipelines and executable scripts. Implement basic algorithms in Python, focusing on time efficiency and structured programming. Who This Book Is For Experienced researchers looking to improve their computational skills; students in the natural sciences and engineering; scientists and engineers from various fields, seeking to integrate programming skills into their research methodologies.
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Mastering Python Scripting for System Administrators
Leverage the features and libraries of Python to administrate your environment efficiently.Key FeaturesLearn how to solve problems of system administrators and automate routine activitiesLearn to handle regular expressions, network administration Building GUI, web-scraping and database administration including data analyticsBook DescriptionPython has evolved over time and extended its features in relation to every possible IT operation. Python is simple to learn, yet has powerful libraries that can be used to build powerful Python scripts for solving real-world problems and automating administrators' routine activities. The objective of this book is to walk through a series of projects that will teach readers Python scripting with each project.This book will initially cover Python installation and quickly revise basic to advanced programming fundamentals. The book will then focus on the development process as a whole, from setup to planning to building different tools. It will include IT administrators' routine activities (text processing, regular expressions, file archiving, and encryption), network administration (socket programming, email handling, the remote controlling of devices using telnet/ssh, and protocols such as SNMP/DHCP), building graphical user interface, working with websites (Apache log file processing, SOAP and REST APIs communication, and web scraping), and database administration (MySQL and similar database data administration, data analytics, and reporting).By the end of this book, you will be able to use the latest features of Python and be able to build powerful tools that will solve challenging, real-world tasksWhat you will learnUnderstand how to install Python and debug Python scriptsUnderstand and write scripts for automating testing and routine administrative activitiesUnderstand how to write scripts for text processing, encryption, decryption, and archivingHandle files, such as pdf, excel, csv, and txt files, and generate reportsWrite scripts for remote network administration, including handling emailsBuild interactive tools using a graphical user interfaceHandle Apache log files, SOAP and REST APIs communicationAutomate database administration and perform statistical analysisWho this book is forThis book would be ideal for users with some basic understanding of Python programming and who are interested in scaling their programming skills to command line scripting and system administration. Prior knowledge of Python would be necessary.
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Learning Professional Python
Volume 1 of Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in the IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills.Learning Professional Python Objectives, Volume 1:Become familiar with the features of Python programming languageIntroduce the object-oriented programming conceptsDiscover how to write Python code by following the object-oriented programming concepts
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Python for Experimental Psychologists
Python for Experimental Psychologists equips researchers who have no prior programming experience with the essential knowledge to independently script experiments and analyses in the programming language Python. The book offers an excellent introduction, whether you are an undergraduate, a PhD candidate, or an established researcher.This updated edition is on Python 3 (the most current version). It starts by teaching the fundamentals of programming in Python, and then offers several chapters on scripting experiments (displaying stimuli, obtaining and logging user input, precision timing, etc.) using the popular PsychoPy package. The remainder of the book is dedicated to data analysis, and includes chapters on reading/writing to text files, time series, eye tracking, data visualisation, and statistics.Access to a companion website enriches the learning experience with colour figures, example stimuli, datasets, scripts, and a portable Windows installation of Python. The book assumes no prior knowledge, and its informal and accessible tone helps readers with backgrounds in experimental psychology and cognitive neuroscience to quickly understand Python. It serves as a useful resource not only for researchers in these fields, but also for lecturers instructing on methodology and data analysis.Python for Experimental Psychologists demystifies programming complexities, and empowers researchers to proficiently conduct experiments and to analyse their results.
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