Articles by "Python"

Showing posts with label Python. Show all posts

J. Burton Browning, Marty Alchin ... 384 pages - Publisher: Apress; 2nd edition (December, 2014) ... Language: English - ISBN-10: 1484203356 - ISBN-13: 978-1484203354.

You’ve learned the basics of Python, but how do you take your skills to the next stage? Even if you know enough to be productive, there are a number of features that can take you to the next level in Python. Pro Python, Second Edition explores concepts and features normally left to experimentation, allowing you to be even more productive and creative. In addition to pure code concerns, Pro Python develops your programming techniques and approaches, which will help make you a better Python programmer. This book will improve not only your code but also your understanding and interaction with the many established Python communities. This book takes your Python knowledge and coding skills to the next level. It shows you how to write clean, innovative code that will be respected by your peers. With this book, make your code do more with introspection and meta-programming. And learn and later use the nuts and bolts of an application, tier-by-tier as a complex case study along the way.

What you’ll learn: Write strong Python code that will be respected in the Python community + Understand the reasons behind big design decisions in Python + Write programs that can reconfigure themselves in Python + Disguise your code as different types of objects in Python + Inspect just about any object in Python + Prepare your code for international audiences + Ensure code quality with rigorous testing. Who this book is for: This book is for intermediate to advanced Python programmers who are looking to understand how and why Python works the way it does and how they can take their code to the next level.

Jonathan Yates ... 170 pages - Publisher: UnKnown; (July, 2016) ... Language: English - ASIN: B01I5P72PC by Amazon.

Are you aware that websites like Instagram, Spotify, and Pinterest use Python Programming in to make their sites? Will you create the next Instagram with your newfound expertise in Python? Python Programming is a widely used language that anyone can use and get good with, and also a super concise language that you can create nearly anything with. Mac, Linux, UNIX, and others have Python installed as a default setting since it is an open source and free language. After you read this book, you will fluent in this versatile code language and see it applied to a variety of examples now with pictures! As stated, you can use the language to create everything you want; a website, make a game, or even create a search engine. The big plus of using Python is, an explicit compiler is not necessary since it’s an entirely interpreted language like Perl, Shell, and others.

Connor P. Milliken ... 332 pages - Publisher: Apress; (November, 2019) ... Language: English - ASIN: B081LWB7FK by Amazon.

Immerse yourself in learning Python and introductory data analytics with this book’s project-based approach. Through the structure of a ten-week coding bootcamp course, you’ll learn key concepts and gain hands-on experience through weekly projects. Each chapter in this book is presented as a full week of topics, with Monday through Thursday covering specific concepts, leading up to Friday, when you are challenged to create a project using the skills learned throughout the week. Topics include Python basics and essential intermediate concepts such as list comprehension, generators and iterators, understanding algorithmic complexity, and data analysis with pandas. From beginning to end, this book builds up your abilities through exercises and challenges, culminating in your solid understanding of Python.

Challenge yourself with the intensity of a coding bootcamp experience or learn at your own pace. With this hands-on learning approach, you will gain the skills you need to jumpstart a new career in programming or further your current one as a software developer. 

What You Will Learn: Understand beginning and more advanced concepts of the Python language + Be introduced to data analysis using pandas, the Python Data Analysis library + Walk through the process of interviewing and answering technical questions + Create real-world applications with the Python language + Learn how to use Anaconda, Jupyter Notebooks, and the Python Shell. Who This Book Is For: Those trying to jumpstart a new career into programming, and those already in the software development industry and would like to learn Python programming.

Pramod Singh, Avinash Manure ... 164 pages - Publisher: Apress; (December, 2019) ... Language: English - ASIN: B082X9CM42 by Amazon.

Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples: The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build models using customer estimators. Further, it explains how to use TensorFlow 2.0 API to build machine learning and deep learning models for image classification using the standard as well as custom parameters. You'll review sequence predictions, saving, serving, deploying, and standardized datasets, and then deploy these models to production. All the code presented in the book will be available in the form of executable scripts at Github which allows you to try out the examples and extend them in interesting ways.

What You'll Learn: Review the new features of TensorFlow 2.0 + Use TensorFlow 2.0 to build machine learning and deep learning models + Perform sequence predictions using TensorFlow 2.0 + Deploy TensorFlow 2.0 models with practical examples

Sebastian Raschka, Vahid Mirjalili ... 770 pages - Publisher: Packt Publishing; (December, 2019) ... Language: English - ISBN-10: 1789955750 - ISBN-13: 978-1789955750.

Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.

What you will learn: Master the frameworks, models, and techniques that enable machines to 'learn' from data + Use scikit-learn for machine learning and TensorFlow for deep learning + Apply machine learning to image classification, sentiment analysis, intelligent web applications, and more + Build and train neural networks, GANs, and other models + Discover best practices for evaluating and tuning models + Predict continuous target outcomes using regression analysis + Dig deeper into textual and social media data using sentiment analysis

Joel Grus ... 406 pages - Publisher: O'Reilly Media; 2nd edition (May, 2019) ... Language: English - ISBN-10: 1492041130 - ISBN-13: 978-1492041139.

To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, and toolkits—but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today’s messy glut of data.

Yves J. Hilpisch ... 720 pages - Publisher: O'Reilly Media; 2nd edition (January, 2019) ... Language: English - ISBN-10: 1492024333 - ISBN-13: 978-1492024330.

The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full fledged framework for Monte Carlo simulation based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.

Kevin Lioy ... 127 pages - Publisher: Independently Published; (November, 2019) ... Language: English - ISBN-10: 1704429161 - ISBN-13: 978-1704429168.

Python Advanced Programming approaches this programming language in a very practical method to make sure you can learn everything you need to start working with Python as soon as possible and to handle advanced feature of this unique language. You will learn: Advanced procedural programming techniques. What is Dynamic Code Execution. Advanced OOP functions most developers are not aware of. Functional-style programming with Python. How to debug, test and profile your software. How to handle multiple processes. The best techniques to spread the workload on different threads.

Andreas Müller, Sarah Guido ... 400 pages - Publisher: O'Reilly Media; (October, 2016) ... Language: English - ISBN-10: 1449369413 - ISBN-13: 978-1449369415.

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. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.

With this book, you’ll learn: Fundamental concepts and applications of machine learning + Advantages and shortcomings of widely used machine learning algorithms + How to represent data processed by machine learning, including which data aspects to focus on + Advanced methods for model evaluation and parameter tuning + The concept of pipelines for chaining models and encapsulating your workflow + Methods for working with text data, including text-specific processing techniques + Suggestions for improving your machine learning and data science skills.

Gowrishankar S., Veena A. ... 464 pages - Publisher: Chapman and Hall/CRC; (November, 2018) ... Language: English - ISBN-10: 0815394373 - ISBN-13: 978-0815394372

Introduction to Python Programming is written for students who are beginners in the field of computer programming. This book presents an intuitive approach to the concepts of Python Programming for students. This book differs from traditional texts not only in its philosophy but also in its overall focus, level of activities, development of topics, and attention to programming details. The contents of the book are chosen with utmost care after analyzing the syllabus for Python course prescribed by various top universities in USA, Europe, and Asia. Since the prerequisite know-how varies significantly from student to student, the book’s overall overture addresses the challenges of teaching and learning of students which is fine-tuned by the authors’ experience with large sections of students. This book uses natural language expressions instead of the traditional shortened words of the programming world. This book has been written with the goal to provide students with a textbook that can be easily understood and to make a connection between what students are learning and how they may apply that knowledge.

Silas Toms ... 210 pages - Publisher: Packt Publishing; (February, 2015) ... Language: English - ISBN-10: 1783988665 - ISBN-13: 978-1783988662.

Use the ArcPy module to automate the analysis and mapping of geospatial data in ArcGIS: Perform GIS analysis faster by automating tasks, such as selecting data or buffering data, by accessing GIS tools using scripting. Access the spatial data contained within shapefiles and geodatabases, for updates, analysis and even transformation between spatial reference systems. Produce map books and automate the mapping of geospatial analyses, reducing the time needed to produce and display the results. Who This Book Is For: If you are a GIS student or professional who needs an understanding of how to use ArcPy to reduce repetitive tasks and perform analysis faster, this book is for you. It is also a valuable book for Python programmers who want to understand how to automate geospatial analyses. What You Will Learn: Understand how to integrate Python into ArcGIS and make GIS analysis faster and easier + Model an analysis and export it to Python for further improvement + Create Python functions from exported scripts using ArcToolbox tools to avoid repetitive code + Update the records of interest in your existing geospatial data automatically using data cursors + Add new geospatial data to existing datasets automatically from field-collected data or data produced during analysis + Export formatted analysis results to spreadsheets automatically + Update map documents with analysis-generated data and export maps to PDF or image formats + Create geometric networks and analyze routes using scripts.

Benjamin Baka ... 312 pages - Publisher: Packt Publishing; (May, 2017) ... Language: English - ASIN: B01IF7NLM8 by Amazon ...

Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications.

Kent D. Lee, Steve Hubbard ... 363 pages - Publisher: Springer; (January, 2015) ... Language: English- ISBN-10: 3319130714 - ISBN-13: 978-3319130712 ...

This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. Features: includes both introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses provided in the preface; provides learning goals, review questions and programming exercises in each chapter, as well as numerous illustrative examples; offers downloadable programs and supplementary files at an associated website, with instructor materials available from the author; presents a primer on Python for those from a different language background.

Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser ... 748 pages - Publisher: Wiley India; (October, 2013) ... Language: English - ISBN-10: 1118290275 - ISBN-13: 978-1118290279 ...

Based on the authors’ market leading data structures books in Java and C++, this book offers a comprehensive, definitive introduction to data structures in Python by authoritative authors. Data Structures and Algorithms in Python is the first authoritative object-oriented book available for Python data structures. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++.Begins by discussing Python’s conceptually simple syntax, which allows for a greater focus on concepts. Employs a consistent object-oriented viewpoint throughout the text. Presents each data structure using ADTs and their respective implementations and introduces important design patterns as a means to organize those implementations into classes, methods, and objects. Provides a thorough discussion on the analysis and design of fundamental data structures. Includes many helpful Python code examples, with source code provided on the website. Uses illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Provides hundreds of exercises that promote creativity, help readers learn how to think like programmers, and reinforce important concepts. Contains many Python-code and pseudo-code fragments, and hundreds of exercises, which are divided into roughly 40% reinforcement exercises, 40% creativity exercises, and 20% programming projects.

The topics in this course come from an analysis of real requirements in data scientist job listings from the biggest tech employers. We'll cover the machine learning, AI, and data mining techniques real employers are looking for, including: Deep Learning / Neural Networks (MLP's, CNN's, RNN's) with TensorFlow and Keras + Sentiment analysis + Image recognition and classification + Regression analysis + K-Means Clustering + Principal Component Analysis + Train/Test and cross validation + Bayesian Methods + Decision Trees and Random Forests + Multivariate Regression + Multi-Level Models + Support Vector Machines + Reinforcement Learning + Collaborative Filtering + K-Nearest Neighbor + Bias/Variance Tradeoff + Ensemble Learning + Term Frequency / Inverse Document Frequency + Experimental Design and A/B Tests.

Luca Massaron ... 312 pages - Publisher: Packt Publishing; (February, 2016) ... Language: English - ISBN-10: 1785286315 - ISBN-13: 978-1785286315 ...

Regression is the process of learning relationships between inputs and continuous outputs from example data, which enables predictions for novel inputs. There are many kinds of regression algorithms, and the aim of this book is to explain which is the right one to use for each set of problems and how to prepare real-world data for it. With this book you will learn to define a simple regression problem and evaluate its performance. The book will help you understand how to properly parse a dataset, clean it, and create an output matrix optimally built for regression. You will begin with a simple regression algorithm to solve some data science problems and then progress to more complex algorithms. The book will enable you to use regression models to predict outcomes and take critical business decisions. Through the book, you will gain knowledge to use Python for building fast better linear models and to apply the results in Python or in any computer language you prefer.

Cyberpunk University ... 126 pages - Publisher: CreateSpace Independent Publishing; (January, 2017) ... Language: English - ISBN-10: 1542589401 - ISBN-13: 978-1542589406 ...

What if you could automate your life to make it much easier? How about, building your own API’s, messaging bots or create an automated coffee machine to make you coffee at the right time with the perfect temperature. Sounds good? This is just a fraction of what you could do with Python and we would love to show you how in just 12 Hours! Bullsh*t you say? Here at Cyberpunk University, we believe that we have the ability to learn Python to anybody within 12 hours. We know how quite tricky it is to learn and be a master of any programming language. Our team is comprised of professionals who have been in the industry of information technology for decades and our experience made us able to create information products such as this step-by-step guide. We took out all the bullsh*t and tell you what to do, and more important, HOW TO DO IT! What will you find in this book: - How to setup the programming language of the future - How to run Hello World the RIGHTWAY - How to use all the different data types in Python - Exercises at the end of each chapter to help you master Python - How to handle errors and exceptions when writing a program - How you can test your programs.

Wes McKinney ... 544 pages - Publisher: O'Reilly Media; 2nd edition (October, 2017) ... Language: English - ISBN-10: 1491957662 - ISBN-13: 978-1491957660 ... 

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing * Learn basic and advanced features in NumPy (Numerical Python) * Get started with data analysis tools in the pandas library * Use flexible tools to load, clean, transform, merge, and reshape data * Create informative visualizations with matplotlib * Apply the pandas groupby facility to slice, dice, and summarize datasets * Analyze and manipulate regular and irregular time series data * Learn how to solve real-world data analysis problems with thorough, detailed examples.

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