Böcker av Oswald Campesato

No detailed description available for "Statistics for Data Scient PB".

This book is designed for data scientists, machine learning practitioners, and anyone with a foundational understanding of Python 3.x. In the evolving field of data science, the ability to manipulate and understand datasets is crucial. The book offers content for mastering these skills using Python 3. The book provides a fast-paced introduction to

This book is designed to show readers the concepts of Python 3 programming and the art of data visualization. It also explores cutting-edge techniques using ChatGPT/GPT-4 in harmony with Python for generating visuals that tell more compelling data stories. Chapter 1 introduces the essentials of Python, covering a vast array of topics from basic dat

This resource is designed to bridge the gap between theoretical understanding and practical application, making it a useful tool for software developers, data scientists, AI researchers, and tech enthusiasts interested in harnessing the power of GPT-4 in Python environments. The book contains an assortment of Python 3.x code samples that were gener

This book is designed for those new to Java and interested in understanding how ChatGPT/GPT-4 can enhance programming. It offers a unique approach to learning Java, combining traditional hand-written code with cutting-edge ChatGPT-generated examples. The book covers the basics of Java programming and development environments, including understandin

This book is intended primarily for people who want to learn both Python 3 and how to use ChatGPT with Python. Chapter One begins with an introduction to fundamental aspects of Python programming, including various data types, number formatting, Unicode and UTF-8 handling, and text manipulation techniques. Later, the book covers loops, conditional

No detailed description available for "Transformer BERT and GPT3 P".

The purpose of this book is to usher readers into the world of data, ensuring a comprehensive understanding of its nuances, intricacies, and complexities. With Python 3 as the primary medium, the book underscores the pivotal role of data in modern industries, and how its adept management can lead to insightful decision-making. The book provides a q

Python 3 and Data Visualization offers readers a deep dive into the world of Python 3 programming and the art of data visualization. Chapter 1 introduces the essentials of Python, covering a vast array of topics from basic data types, loops, and functions to more advanced constructs like dictionaries, sets, and matrices. In Chapter 2, the focus shi

This book eases you into the foundational aspects of Python 3.x with an extensive range of code samples that illustrate its diverse features. Start with Python tools and installations, and progressively learn intricacies like strings, loops, conditional logic, and much more. The appendices on NumPy and Pandas provide insights into efficient numeric

This book provides relevant information about intermediate Python 3.x for a variety of topics, such as comprehensions, iterators, generators, regular expressions, OOP, queues and stacks, and recursion. Each chapter contains an assortment of code samples that illustrate the topics in the chapter material. It assumes the reader is already familiar with Python programming and wants to expand programming skills in order to use Python in a variety of subject areas and disciplines such as business, mathematics, science, and engineering. Knowledge of other programming languages (such as Java) can also be helpful because of the exposure to programming concepts and object-oriented programming. This book includes companion files with numerous code samples, figures, and applications from the text.

No detailed description available for "Linux Shell Programming Pocket Primer".

This book is a fast-paced introduction to using data structures with Java. Numerous code samples and listings are included to support myriad topics. The first chapter contains a quick introduction to Java, along with Java code samples to check for leap years, find divisors of a number, and work with arrays of strings. The second chapter introduces

This book contains a fast-paced introduction to data-related tasks in preparation for training models on datasets. It presents a step-by-step, Python-based code sample that uses the kNN algorithm to manage a model on a dataset.Chapter One begins with an introduction to datasets and issues that can arise, followed by Chapter Two on outliers and anomaly detection. The next chapter explores ways for handling missing data and invalid data, and Chapter Four demonstrates how to train models with classification algorithms. Chapter 5 introduces visualization toolkits, such as Sweetviz, Skimpy, Matplotlib, and Seaborn, along with some simple Python-based code samples that render charts and graphs. An appendix includes some basics on using awk. Companion files with code, datasets, and figures are available for downloading.Features: Covers extensive topics related to cleaning datasets and working with models Includes Python-based code samples and a separate chapter on Matplotlib and Seaborn Features companion files with source code, datasets, and figures from the book

No detailed description available for "Bash for Data Scientists".

No detailed description available for "Pandas Basics".

No detailed description available for "Python Data Structures Pocket Primer".

No detailed description available for "Data Wrangling Using Pandas, SQL, and Java".

No detailed description available for "Python Tools for Data Scientists Pocket Primer".

As part of the best-selling Pocket Primer series, this book is designed to provide a thorough introduction to Java development for people who are relatively new to the Java programming language. It is intended to be a fast-paced introduction to the core concepts of Java and Java APIs, illustrated with code samples using primarily Java 8. Companion

No detailed description available for "Python for Programmers".

No detailed description available for "C Programming Pocket Primer".

As part of the best-selling Pocket Primer series, this book is primarily for data scientists and machine learning engineers who want to expand their current knowledge of SQL using MySQL as the primary RDBMS. It includes Python-based code samples to access data from a MySQL table in a Pandas data frame and Java-based code samples for accessing data in a MySQL database, along with XML documents and JSON documents. The book also introduces NoSQL, presents an overview of MongoDB, and SQLite--an open-source RDBMS availableon mobile devices. The final chapter of the book covers a diverse set of miscellaneous topics, such as normalization, schemas, database optimization, and performance. Numerous code samples and listings are included to support myriad topics. Companion files with source code and figures are available from the publisher. FEATURES: Covers extensive topics related to SQL, using MySQL as the primary RDBMSIntroduces NoSQL, presents an overview of MongoDB, and SQLite--an open-source RDBMS available on mobile devicesFeatures companion files with source code and figures from the book

A book for developers who are looking for an overview of basic concepts in Natural Language Processing using R. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics.

A book for developers who are looking for an overview of basic concepts in Natural Language Processing. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics.

Presents a short tour of basic Angular functionality, such as UI components and forms in Angular applications; introduces machine learning concepts; cpvers classification algorithms, such as kNN, and Naive Bayes; and introduces basic TensorFlow concepts.

As part of the best-selling Pocket Primer series, this book is meant to familiarize readers with regular expressions as part of their data-related tasks. Regular expressions (regex) are used in search engines, search and replace dialogs of word processors and text editors, in text processing utilities such as sed and awk, and in lexical analysis. Many programming languages provide regex capabilities, either built-in or via libraries. Readers will learn how to use bash commands grep, awk, and sed in order to use regular expressions in conjunction with datasets and data-related tasks. Companion files with source code are available for downloading from the publisher.Features:* A practical introduction to using flexible, bash commands to perform common data cleaning tasks* Assumes the reader has no prior experience, but the topic is covered comprehensively enough to teach a pro some new tricks*Simple yet powerful shell scripts for data cleaning tasks

As part of the bestselling Pocket Primer series, this book is an effort to give programmers sufficient knowledge of data cleaning to be able to work on their own projects. It is designed as a practical introduction to using flexible, powerful (and free) Unix / Linux shell commands to perform common data cleaning tasks.

Covers the features of HTML5 Canvas, CSS3 graphics, and shows how to extend the power of CSS3 with SVG. The material in this book is accessible to people who have limited knowledge of HTML and JavaScript. A companion DVD with source code and graphics is included.

A book for developers who are looking for an introduction to basic concepts in NLP and machine learning. Numerous code samples and listings are included to support myriad topics. Includes introductory material for NumPy and Pandas, followed by NLP concepts, algorithms and toolkits, machine learning, and NLP applications.