Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Python Calendar 2021
Download Python Calendar 2021 full books in PDF, epub, and Kindle. Read online Python Calendar 2021 ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Learn Python Programming Systematically and Step by Step by : Chaitanya Patil
Download or read book Learn Python Programming Systematically and Step by Step written by Chaitanya Patil and published by Chaitanya Patil. This book was released on with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python is immensely popular and one of the most highly-demanded programming languages in the world. You can learn Python Programming Systematically and Step by Step by referring to this eBook. Refer to the Video Course for more clarity.
Book Synopsis Learn Python Programming by : Fabrizio Romano
Download or read book Learn Python Programming written by Fabrizio Romano and published by Packt Publishing Ltd. This book was released on 2021-10-29 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up and running with Python 3.9 through concise tutorials and practical projects in this fully updated third edition. Purchase of the print or Kindle book includes a free eBook in PDF format. Key FeaturesExtensively revised with richer examples, Python 3.9 syntax, and new chapters on APIs and packaging and distributing Python codeDiscover how to think like a Python programmerLearn the fundamentals of Python through real-world projects in API development, GUI programming, and data scienceBook 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 learnGet Python up and running on Windows, Mac, and LinuxWrite elegant, reusable, and efficient code in any situationAvoid common pitfalls like duplication, complicated design, and over-engineeringUnderstand when to use the functional or object-oriented approach to programmingBuild a simple API with FastAPI and program GUI applications with TkinterGet an initial overview of more complex topics such as data persistence and cryptographyFetch, clean, and manipulate data, making efficient use of Python's built-in data structuresWho this book is for This book is for everyone who wants to learn Python from scratch, as well as experienced programmers looking for a reference book. Prior knowledge of basic programming concepts will help you follow along, but it's not a prerequisite.
Book Synopsis Machine Learning for Time-Series with Python by : Ben Auffarth
Download or read book Machine Learning for Time-Series with Python written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2021-10-29 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get better insights from time-series data and become proficient in model performance analysis Key FeaturesExplore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time series via real-world case studies on operations management, digital marketing, finance, and healthcareBook Description The Python time-series ecosystem is huge and often quite hard to get a good grasp on, especially for time-series since there are so many new libraries and new models. This book aims to deepen your understanding of time series by providing a comprehensive overview of popular Python time-series packages and help you build better predictive systems. Machine Learning for Time-Series with Python starts by re-introducing the basics of time series and then builds your understanding of traditional autoregressive models as well as modern non-parametric models. By observing practical examples and the theory behind them, you will become confident with loading time-series datasets from any source, deep learning models like recurrent neural networks and causal convolutional network models, and gradient boosting with feature engineering. This book will also guide you in matching the right model to the right problem by explaining the theory behind several useful models. You'll also have a look at real-world case studies covering weather, traffic, biking, and stock market data. By the end of this book, you should feel at home with effectively analyzing and applying machine learning methods to time-series. What you will learnUnderstand the main classes of time series and learn how to detect outliers and patternsChoose the right method to solve time-series problemsCharacterize seasonal and correlation patterns through autocorrelation and statistical techniquesGet to grips with time-series data visualizationUnderstand classical time-series models like ARMA and ARIMAImplement deep learning models, like Gaussian processes, transformers, and state-of-the-art machine learning modelsBecome familiar with many libraries like Prophet, XGboost, and TensorFlowWho this book is for This book is ideal for data analysts, data scientists, and Python developers who want instantly useful and practical recipes to implement today, and a comprehensive reference book for tomorrow. Basic knowledge of the Python Programming language is a must, while familiarity with statistics will help you get the most out of this book.
Book Synopsis Python Programming for Data Analysis by : José Unpingco
Download or read book Python Programming for Data Analysis written by José Unpingco and published by Springer Nature. This book was released on 2021-05-04 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of California, San Diego, which is a requirement for both graduate and undergraduate degrees in Machine Learning and Data Science. This book is ideal for readers with some Python programming experience. The book covers key language concepts that must be understood to program effectively, especially for data analysis applications. Certain low-level language features are discussed in detail, especially Python memory management and data structures. Using Python effectively means taking advantage of its vast ecosystem. The book discusses Python package management and how to use third-party modules as well as how to structure your own Python modules. The section on object-oriented programming explains features of the language that facilitate common programming patterns. After developing the key Python language features, the book moves on to third-party modules that are foundational for effective data analysis, starting with Numpy. The book develops key Numpy concepts and discusses internal Numpy array data structures and memory usage. Then, the author moves onto Pandas and details its many features for data processing and alignment. Because strong visualizations are important for communicating data analysis, key modules such as Matplotlib are developed in detail, along with web-based options such as Bokeh, Holoviews, Altair, and Plotly. The text is sprinkled with many tricks-of-the-trade that help avoid common pitfalls. The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis. To get the most out of this book, open a Python interpreter and type along with the many code samples.
Book Synopsis Chase's Calendar of Events 2021 by : Editors of Chase's
Download or read book Chase's Calendar of Events 2021 written by Editors of Chase's and published by Rowman & Littlefield. This book was released on 2020-10-27 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: Find out what's going on any day of the year, anywhere across the globe! The world’s date book since 1957, Chase's is the definitive, authoritative, day-by-day resource of what the world is celebrating and commemorating. From national days to celebrity birthdays, from historical anniversaries to astronomical phenomena, from award ceremonies and sporting events to religious festivals and carnivals, Chase's is the must-have reference used by experts and professionals—a one-stop shop with 12,500 entries for everything that is happening now or is worth remembering from the past. Completely updated for 2021, Chase's also features extensive appendices as well as a companion website that puts the power of Chase's at the user's fingertips. 2021 is packed with special events and observances, including National days and public holidays of every nation on Earth The 400th anniversary of the Plymouth pilgrim Thanksgiving The 200th independence anniversary from Spain of its Central and South American colonies. The 100th anniversary of the Tulsa Race Massacre Scores of new special days, weeks and months Birthdays of new world leaders, office holders, and breakout stars And much more! All from the reference book that Publishers Weekly calls "one of the most impressive reference volumes in the world."
Book Synopsis "Python Mastery: A Complete Guide to Programming Excellence" by : RAMANA
Download or read book "Python Mastery: A Complete Guide to Programming Excellence" written by RAMANA and published by RAMANA. This book was released on 2024-04-18 with total page 3830 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is a description for the book *"Python Mastery: A Complete Guide to Programming Excellence"*: Unlock your full potential as a programmer with *"Python Mastery: A Complete Guide to Programming Excellence"*. This comprehensive book is designed to guide you from the fundamentals of Python programming to advanced concepts and best practices. Through clear explanations and hands-on exercises, you'll gain a solid understanding of core topics such as data types, control structures, functions, and modules. Dive deeper into object-oriented programming, file handling, and libraries like NumPy and Pandas. Explore powerful techniques for debugging, testing, and optimizing your code. Whether you're a beginner or an experienced developer, this guide will help you achieve mastery in Python and elevate your programming skills to new heights.
Book Synopsis Python Tools for Scientists by : Lee Vaughan
Download or read book Python Tools for Scientists written by Lee Vaughan and published by No Starch Press. This book was released on 2023-01-17 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the Python programming language and its most popular tools for scientists, engineers, students, and anyone who wants to use Python for research, simulations, and collaboration. Python Tools for Scientists will introduce you to Python tools you can use in your scientific research, including Anaconda, Spyder, Jupyter Notebooks, JupyterLab, and numerous Python libraries. You’ll learn to use Python for tasks such as creating visualizations, representing geospatial information, simulating natural events, and manipulating numerical data. Once you’ve built an optimal programming environment with Anaconda, you’ll learn how to organize your projects and use interpreters, text editors, notebooks, and development environments to work with your code. Following the book’s fast-paced Python primer, you’ll tour a range of scientific tools and libraries like scikit-learn and seaborn that you can use to manipulate and visualize your data, or analyze it with machine learning algorithms. You’ll also learn how to: Create isolated projects in virtual environments, build interactive notebooks, test code in the Qt console, and use Spyder’s interactive development features Use Python’s built-in data types, write custom functions and classes, and document your code Represent data with the essential NumPy, Matplotlib, and pandas libraries Use Python plotting libraries like Plotly, HoloViews, and Datashader to handle large datasets and create 3D visualizations Regardless of your scientific field, Python Tools for Scientists will show you how to choose the best tools to meet your research and computational analysis needs.
Book Synopsis Mastering Tableau 2021 by : Marleen Meier
Download or read book Mastering Tableau 2021 written by Marleen Meier and published by Packt Publishing Ltd. This book was released on 2021-05-31 with total page 793 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build, design, and improve advanced business intelligence solutions using Tableau's latest features, including Tableau Prep Builder, Tableau Hyper, and Tableau Server Key FeaturesMaster new features in Tableau 2021 to solve real-world analytics challengesPerform geo-spatial, time series, and self-service analytics using real-life examplesBuild and publish dashboards and explore storytelling using Python and R integration supportBook Description Tableau is one of the leading business intelligence (BI) tools that can help you solve data analysis challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain. Updated with fresh topics including Quick Level of Detail expressions, the newest Tableau Server features, Einstein Discovery, and more, this book covers essential Tableau concepts and advanced functionalities. Leveraging Tableau Hyper files and using Prep Builder, you'll be able to perform data preparation and handling easily. You'll gear up to perform complex joins, spatial joins, unions, and data blending tasks using practical examples. Next, you'll learn how to execute data densification and further explore expert-level examples to help you with calculations, mapping, and visual design using Tableau extensions. You'll also learn about improving dashboard performance, connecting to Tableau Server and understanding data visualization with examples. Finally, you'll cover advanced use cases such as self-service analysis, time series analysis, and geo-spatial analysis, and connect Tableau to Python and R to implement programming functionalities within it. By the end of this Tableau book, you'll have mastered the advanced offerings of Tableau 2021 and be able to tackle common and advanced challenges in the BI domain. What you will learnGet up to speed with various Tableau componentsMaster data preparation techniques using Tableau Prep BuilderDiscover how to use Tableau to create a PowerPoint-like presentationUnderstand different Tableau visualization techniques and dashboard designsInteract with the Tableau server to understand its architecture and functionalitiesStudy advanced visualizations and dashboard creation techniquesBrush up on powerful self-service analytics, time series analytics, and geo-spatial analyticsWho this book is for This book is designed for business analysts, business intelligence professionals and data analysts who want to master Tableau to solve a range of data science and business intelligence problems. The book is ideal if you have a good understanding of Tableau and want to take your skills to the next level.
Book Synopsis Python for SAS Users by : Randy Betancourt
Download or read book Python for SAS Users written by Randy Betancourt and published by Apress. This book was released on 2019-09-06 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business users familiar with Base SAS programming can now learn Python by example. You will learn via examples that map SAS programming constructs and coding patterns into their Python equivalents. Your primary focus will be on pandas and data management issues related to analysis of data. It is estimated that there are three million or more SAS users worldwide today. As the data science landscape shifts from using SAS to open source software such as Python, many users will feel the need to update their skills. Most users are not formally trained in computer science and have likely acquired their skills programming SAS as part of their job. As a result, the current documentation and plethora of books and websites for learning Python are technical and not geared for most SAS users. Python for SAS Users provides the most comprehensive set of examples currently available. It contains over 200 Python scripts and approximately 75 SAS programs that are analogs to the Python scripts. The first chapters are more Python-centric, while the remaining chapters illustrate SAS and corresponding Python examples to solve common data analysis tasks such as reading multiple input sources, missing value detection, imputation, merging/combining data, and producing output. This book is an indispensable guide for integrating SAS and Python workflows. What You’ll Learn Quickly master Python for data analysis without using a trial-and-error approach Understand the similarities and differences between Base SAS and Python Better determine which language to use, depending on your needs Obtain quick results Who This Book Is For SAS users, SAS programmers, data scientists, data scientist leaders, and Python users who need to work with SAS
Download or read book Python Programming written by Dr.L.Ramesh and published by SK Research Group of Companies. This book was released on 2024-01-02 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr.L.Ramesh, Assistant Professor, Department of Information Technology, Vels Institute of Science, Technology & Advanced Studies (VISTAS),Pallavaram, Chennai, Tamil Nadu, India. Dr.R.Suresh, Assistant Professor, Department of Computer Applications, DRBCCC Hindu College, Pattabiram, Chennai, Tamil Nadu, India. Dr.S.Gopinathan, Professor & Head, Department of Computer Science, Guindy Campus, University of Madras, Chennai, Tamil Nadu, India.
Book Synopsis Learning R and Python for Business School Students by : Yuxing Yan
Download or read book Learning R and Python for Business School Students written by Yuxing Yan and published by Cambridge Scholars Publishing. This book was released on 2022-11-04 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a guide for business school students, individual investors, and business professionals to learn R and Python, two open-source programming languages. It is unique since it allows the reader to learn programming in an “R-assisted learning environment”. The book provides 15 weeks’ worth of teaching material for the reader.
Book Synopsis Time Series Analysis with Python Cookbook by : Tarek A. Atwan
Download or read book Time Series Analysis with Python Cookbook written by Tarek A. Atwan and published by Packt Publishing Ltd. This book was released on 2022-06-30 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: Perform time series analysis and forecasting confidently with this Python code bank and reference manual Key Features • Explore forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms • Learn different techniques for evaluating, diagnosing, and optimizing your models • Work with a variety of complex data with trends, multiple seasonal patterns, and irregularities Book Description Time series data is everywhere, available at a high frequency and volume. It is complex and can contain noise, irregularities, and multiple patterns, making it crucial to be well-versed with the techniques covered in this book for data preparation, analysis, and forecasting. This book covers practical techniques for working with time series data, starting with ingesting time series data from various sources and formats, whether in private cloud storage, relational databases, non-relational databases, or specialized time series databases such as InfluxDB. Next, you'll learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods, followed by more advanced unsupervised ML models. The book will also explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR. The recipes will present practical techniques for handling non-stationary data, using power transforms, ACF and PACF plots, and decomposing time series data with multiple seasonal patterns. Later, you'll work with ML and DL models using TensorFlow and PyTorch. Finally, you'll learn how to evaluate, compare, optimize models, and more using the recipes covered in the book. What you will learn • Understand what makes time series data different from other data • Apply various imputation and interpolation strategies for missing data • Implement different models for univariate and multivariate time series • Use different deep learning libraries such as TensorFlow, Keras, and PyTorch • Plot interactive time series visualizations using hvPlot • Explore state-space models and the unobserved components model (UCM) • Detect anomalies using statistical and machine learning methods • Forecast complex time series with multiple seasonal patterns Who this book is for This book is for data analysts, business analysts, data scientists, data engineers, or Python developers who want practical Python recipes for time series analysis and forecasting techniques. Fundamental knowledge of Python programming is required. Although having a basic math and statistics background will be beneficial, it is not necessary. Prior experience working with time series data to solve business problems will also help you to better utilize and apply the different recipes in this book.
Book Synopsis Learning Professional Python by : Usharani Bhimavarapu
Download or read book Learning Professional Python written by Usharani Bhimavarapu and published by CRC Press. This book was released on 2023-10-16 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills. Learning Professional Python: Volume 1 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications
Book Synopsis Essentials of Excel VBA, Python, and R by : John Lee
Download or read book Essentials of Excel VBA, Python, and R written by John Lee and published by Springer Nature. This book was released on 2023-03-23 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data with the applications of Excel VBA, Python and R. Each chapter engages the reader with sample data drawn from individual stocks, stock indices, options, and futures. Now in its second edition, it has been expanded into two volumes, each of which is devoted to specific parts of the business analytics curriculum. To reflect the current age of data science and machine learning, the used applications have been updated from Minitab and SAS to Python and R, so that readers will be better prepared for the current industry. This second volume is designed for advanced courses in financial derivatives, risk management, and machine learning and financial management. In this volume we extensively use Excel, Python, and R to analyze the above-mentioned topics. It is also a comprehensive reference for active statistical finance scholars and business analysts who are looking to upgrade their toolkits. Readers can look to the first volume for dedicated content on financial statistics, and portfolio analysis.
Book Synopsis Metaprogramming with Python by : Sulekha AloorRavi
Download or read book Metaprogramming with Python written by Sulekha AloorRavi and published by Packt Publishing Ltd. This book was released on 2022-09-09 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical approach to metaprogramming with real-world examples that enables the development of advanced frameworks, libraries, and applications using Python Key FeaturesLearn applied metaprogramming through a simple step-by-step approachWork with easily understandable examples and explanations that take you deep into the theory of metaprogrammingGet practical experience in writing reusable code with real-world examplesBook Description Effective and reusable code makes your application development process seamless and easily maintainable. With Python, you will have access to advanced metaprogramming features that you can use to build high-performing applications. The book starts by introducing you to the need and applications of metaprogramming, before navigating the fundamentals of object-oriented programming. Next, you will learn about simple decorators, work with metaclasses, and later focus on introspection and reflection. You'll also delve into generics and typing before defining templates for algorithms. As you progress, you will understand your code using abstract syntax trees and explore method resolution order. This Python book also shows you how to create your own dynamic objects before structuring the objects through design patterns. Finally, you will learn simple code-generation techniques along with discovering best practices and eventually building your own applications. By the end of this learning journey, you'll have acquired the skills and confidence you need to design and build reusable high-performing applications that can solve real-world problems. What you will learnUnderstand the programming paradigm of metaprogramming and its needRevisit the fundamentals of object-oriented programmingDefine decorators and work with metaclassesEmploy introspection and reflection on your codeApply generics, typing, and templates to enhance your codeGet to grips with the structure of your code through abstract syntax trees and the behavior through method resolution orderCreate dynamic objects and generate dynamic codeUnderstand various design patterns and best practicesWho this book is for If you are an intermediate-level Python programmer looking to enhance your coding skills by developing reusable and advanced frameworks, then this book is for you. Basic knowledge of Python programming will help you get the most out of this learning journey.
Book Synopsis The Big Book of Small Python Projects by : Al Sweigart
Download or read book The Big Book of Small Python Projects written by Al Sweigart and published by No Starch Press. This book was released on 2021-06-29 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Best-selling author Al Sweigart shows you how to easily build over 80 fun programs with minimal code and maximum creativity. If you’ve mastered basic Python syntax and you’re ready to start writing programs, you’ll find The Big Book of Small Python Projects both enlightening and fun. This collection of 81 Python projects will have you making digital art, games, animations, counting pro- grams, and more right away. Once you see how the code works, you’ll practice re-creating the programs and experiment by adding your own custom touches. These simple, text-based programs are 256 lines of code or less. And whether it’s a vintage screensaver, a snail-racing game, a clickbait headline generator, or animated strands of DNA, each project is designed to be self-contained so you can easily share it online. You’ll create: • Hangman, Blackjack, and other games to play against your friends or the computer • Simulations of a forest fire, a million dice rolls, and a Japanese abacus • Animations like a virtual fish tank, a rotating cube, and a bouncing DVD logo screensaver • A first-person 3D maze game • Encryption programs that use ciphers like ROT13 and Vigenère to conceal text If you’re tired of standard step-by-step tutorials, you’ll love the learn-by-doing approach of The Big Book of Small Python Projects. It’s proof that good things come in small programs!
Book Synopsis Numerical Python in Astronomy and Astrophysics by : Wolfram Schmidt
Download or read book Numerical Python in Astronomy and Astrophysics written by Wolfram Schmidt and published by Springer Nature. This book was released on 2021-07-14 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a solid foundation in the Python programming language, numerical methods, and data analysis, all embedded within the context of astronomy and astrophysics. It not only enables students to learn programming with the aid of examples from these fields but also provides ample motivation for engagement in independent research. The book opens by outlining the importance of computational methods and programming algorithms in contemporary astronomical and astrophysical research, showing why programming in Python is a good choice for beginners. The performance of basic calculations with Python is then explained with reference to, for example, Kepler’s laws of planetary motion and gravitational and tidal forces. Here, essential background knowledge is provided as necessary. Subsequent chapters are designed to teach the reader to define and use important functions in Python and to utilize numerical methods to solve differential equations and landmark dynamical problems in astrophysics. Finally, the analysis of astronomical data is discussed, with various hands-on examples as well as guidance on astronomical image analysis and applications of artificial neural networks.
