Modern C++ Programming Cookbook - Master Modern C++ with comprehensive solutions for C++23 and all previous standards

Marius Bancila

Sinopse

The updated third edition of Modern C++ Programming Cookbook addresses the latest features of C++23, such as the stacktrace library, std::expected and std::mdspan classes, the  header, formatting library improvements, and updates to the ranges library. It also gets into more C++20 topics not previously covered, such as sync streams and source_location.

The book is organized into practical recipes covering a wide range of real-world problems, helping you find the solutions you need quickly. You’ll find coverage of all the core concepts of modern C++ programming and features and techniques from C++11 through to C++23, meaning you’ll stay ahead of the curve by learning to incorporate the newest language and library improvements.

Beyond the core concepts and new features, you’ll explore recipes related to performance and best practices, how to implement useful patterns and idioms, like pimpl, named parameter, attorney-client, and the factory pattern, and how to complete unit testing with the widely used C++ libraries: Boost.Test, Google Test, and Catch2.

With the comprehensive coverage this C++ programming guide offers, by the end of the book you’ll have everything you need to build performant, scalable, and efficient applications in C++.

Disponível desde: 29/02/2024.

Comprimento de impressão: 816 páginas.

Ciência e Tecnologia

Outros livros que poderiam interessá-lo

Pharmacist Career Planning Audio...

Brian Mahoney

End Money Worries! 
Pharmacist Career Planning Audio Book Bundle  
3 in 1 Career Development Plan Box Set 
Discover... 
* What a Pharmacist does * How to Become a Pharmacist* What is the salary of a Pharmacist 
* What is the Pharmacist Work Environment like * What is the future Job outlook for a Pharmacist 
* How long does it take to become a Pharmacist * How to Prepare for Your Job Interview 
* Tips the pros use to Ace their Job Interview  * You'll be confident with the best answers for the toughest job interview questions 
The knowledge & ability to change your life all for less than the cost of 1 movie ticket! 
 If you are ready to get started & want the knowledge, help & motivation to change your life now!... 
How to start a YouTube Channel & Make Money 
Discover... 
* Why YouTube is Essential for Business Marketing * Creating a YouTube Marketing Strategy 
*Creating Engaging Video Content *Optimizing Your YouTube Channel  
*Monetizing your YouTube Channel *Measuring your YouTube Marketing Success 
*YouTube Shorts Video & Channel Promotion 
So take advantage of this chance for a lifetime passive income stream from YouTube! 
Goal Setting Mastery: A Action Plan to Achieving Your Dreams 
Now you you can take advantage of this goal setting audio book & discover how to achieve success in all aspects of your life: 
* Understanding the Power of Goal Setting * How to set meaningful goals using the SMART Method 
* Creating a Action Plan * Reviewing & adjusting your Goals  * Using Goal Setting in all areas of Your life 
So Don't wait. You'll wait your life away...

Ver livro

Primordium

Lucas Schrader

A New Myth for a New Age!Enjoy the origins of the universe from a new perspective, combining aspects of Christian, Norse, Egyptian, and Greek cosmology.*Primordium, Latin for the first beginning and used in Biology to mean the earliest developmental stage for an organic substructure. These same Latin roots are combined to describe the theoretical swamp where life first began, the primordial soup.

Ver livro

Beyond Quantity - Research with...

Jens Schröter, Andreas Sudmann,...

How do artificial neural networks and other forms of artificial intelligence interfere with methods and practices in the sciences? Which interdisciplinary epistemological challenges arise when we think about the use of AI beyond its dependency on big data? Not only the natural sciences, but also the social sciences and the humanities seem to be increasingly affected by current approaches of subsymbolic AI, which master problems of quality (fuzziness, uncertainty) in a hitherto unknown way. But what are the conditions, implications, and effects of these (potential) epistemic transformations and how must research on AI be configured to address them adequately?

Ver livro

Unraveling the War on Expertise:...

Ronan Ashworthy

Unraveling the War on Expertise: Why We Must Care  
Are you eager to advance in your career and deepen your knowledge in a world where expertise is often undervalued?   
Are you in search of a thorough guide that highlights the importance of valuing authentic expertise and insight?   
Your quest ends here!   
This guide acts as your essential companion for enriching your understanding and engaging with practical exercises. With this resource, you are set up for success.   
Updated for the evolving landscape of 2025.   
Key features of this insightful guide:   
- In-depth analysis of the significance of expertise in today’s society   
- Comprehensive exploration of authentic insight and its benefits   
- Effective strategies for applying knowledge and navigating challenges   
Our guide stands out due to its thorough coverage, which is crucial for your understanding and mastery. Concepts are not just touched upon; they are comprehensively examined.   
Please note, this guide operates independently and is not affiliated with any official organization, ensuring that it is purely a resource for your enrichment.   
Crafted with a clear structure and accessible language, our guide ensures smooth transitions between topics. Say goodbye to convoluted jargon and embrace clear, precise, and technically accurate content.   
So, why delay? Click the BUY NOW button, secure your guide, and embark on your journey toward valuing authentic expertise and insight!

Ver livro

Transforming Ideas into Reality:...

Kellan Ashford

Transforming Ideas into Reality: Secrets to Project Success 
⭐⭐ Simplified Audio Guide with Explanations ⭐⭐ 
Are you aiming to advance in your career and deepen your knowledge by mastering the art of effectively achieving your project goals? 
Looking for a complete guide that offers all the essential elements to unlock strategies for achieving your project goals effectively? 
Your search ends here! 
This book serves as your ultimate companion for broadening your understanding, applying your skills, and engaging in practical exercises. With this, you're set for success. 
Updated for the Project Goal Strategies. 
Key highlights of this enhanced guide: 
- Insightful discussions about effective strategies 
- Detailed explanations on mastering project goal achievements 
- Practical strategies for preparation and tackling challenges 
Our guide sets itself apart with its comprehensive coverage, which is crucial for your success. Concepts aren't just briefly touched upon; they are explored with precision. 
Please note that this guide is an independent resource designed for your benefit and not affiliated with any official entity. 
Crafted with a clear structure and straightforward language, our Project Goal Guide ensures smooth transitions between topics. Say goodbye to dense jargon and embrace clear, precise, and accurate content. 
So, why wait? Click the BUY NOW button, secure your guide, and begin your journey to success in achieving your project goals!

Ver livro

Machine Learning with Python -...

Alexander Cane

Ways to combat retraining depend on the algorithm and consist of the correct values of the trainer's met parameters. In practice, model estimation is not performed on the same input data that was used to train the model. Divide 10-20% of all available data into a separate set and call it a set for evaluation. We will bring the other 10-20% into the set for ratification, and 60-80% of the remaining ones will be given to the trainer. The principle of data sharing depends on the data and the task. Random sampling is often a good method if inputs are independent of each other, and there is no strong imbalance between the number of positive and negative entries.
The intuitive analogy here is the same as with university studies: the teacher solves some problems with students in pairs and gives other’s similar tasks in the exam. What is important here (both in teaching students and models) is that these tasks are varied, and students cannot simply memorize the answers, and those who have mastered the material (similar tasks) will be able to repeat the thought process and answer correctly.
In machine learning, we split into data two sets: we will use the evaluation set to evaluate each model we train, using different approaches, algorithms, and model types to select the best one. That is, for each model, we will have two precision values - precision on the training dataset and precision on the evaluation dataset. It is normal for the former to be higher than the second, but not significantly. A big difference indicates retraining.

Ver livro