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Well-Grounded Python Developer, The - Doug Farrell - Bog - Manning Publications - Plusbog.dk

Algorithms and Data Structures in Action - Marcello La Rocca - Bog - Manning Publications - Plusbog.dk

Algorithms and Data Structures in Action - Marcello La Rocca - Bog - Manning Publications - Plusbog.dk

As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques. about the technology Data structures and algorithms are the foundations for how programs store and process information. Choosing the optimal algorithms ensures that your programs are fast, efficient, and reliable. about the book Algorithms and Data Structures in Action expands on the basic algorithms you already know to give you a better selection of solutions to different programming problems. In it, you’ll discover techniques for improving priority queues, efficient caching, clustering data, and more. Each example is fully illustrated with graphics, language agnostic pseudo-code, and code samples in various languages. When you’re done, you will be able to implement advanced and little-known algorithms to deliver better performance from your code. what''s inside - - Improving on basic data structures - - Efficient caching - - Nearest neighbour search, including k-d trees and S-trees - - Full ‘pseudo-code’ and samples in multiple languages - about the reader For programmers with basic or intermediate skills. Written in a language-agnostic manner, no specific language knowledge is required. about the author Marcello La Rocca is a research scientist and a full-stack engineer focused on optimization algorithms, genetic algorithms, machine learning and quantum computing. He has contributed to large-scale web applications at companies like Twitter and Microsoft, has undertaken applied research in both academia and industry, and authored the Neatsort adaptive sorting algorithm.

DKK 476.00
1

Functional Programming in Scala - Paul Chiusano - Bog - Manning Publications - Plusbog.dk

DKK 364.00
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Python Workout - Reuven Lerner - Bog - Manning Publications - Plusbog.dk

Python Workout - Reuven Lerner - Bog - Manning Publications - Plusbog.dk

Python Workout presents 50 exercises designed to deepen the reader’s skill with Python. Readers will not only tackle exercises using built-in data structures, but also more advanced techniques, such as functional programming, object-oriented programming, iterators, and generators. With each engaging challenge, readers will practice a new skill and learn how to apply it to everyday coding tasks. Key Features - - 50 hands-on exercises and solutions - - Basic Python sequence types - - Python dictionaries and sets - - Functional programming in Python - - Creating your own classes - - Working with Python objects - - Generator functions - Intended for readers with basic Python skills. About the technology Python is a versatile, elegant, general purpose programming language. Essential for data analysis, web development, artificial intelligence, games, desktop apps, and more, Python skills are a hot commodity. Reuven M. Lerner , an independent consultant for more than two decades, teaches Python, data science, and Git to companies around the world. His Better developers newsletter and blog are read by thousands of Python developers each week. Reuven has written a monthly column, “At the Forge,” for Linux Journal since 1996 and is a panellist on the weekly Freelancers Show podcast. Reuven lives with his wife and three children in Modi’in, Israel, and can be reached at https://lerner.co.il/ or on Twitter at @reuvenmlerner.

DKK 448.00
1

Regularization in Deep Learning - Liu Peng - Bog - Manning Publications - Plusbog.dk

Regularization in Deep Learning - Liu Peng - Bog - Manning Publications - Plusbog.dk

Take your deep learning models more adaptable with these practical regularisation techniques. For data scientists, machine learning engineers, and researchers with basic model development experience who want to improve their training efficiency and avoid overfitting errors. Regularization in Deep Learning delivers practical techniques to help you build more general and adaptable deep learning models. It goes beyond basic techniques like data augmentation and explores strategies for architecture, objective function, and optimisation. You will turn regularisation theory into practice using PyTorch, following guided implementations that you can easily adapt and customise to your own model''s needs. Key features include: - - Insights into model generalisability - - A holistic overview of regularisation techniques and strategies - - Classical and modern views of generalisation, including bias and variance tradeoff - - When and where to use different regularisation techniques - - The background knowledge you need to understand cutting-edge research - Along the way, you will get just enough of the theory and mathematics behind regularisation to understand the new research emerging in this important area. About the technology Deep learning models that generate highly accurate results on their training data can struggle with messy real-world test datasets. Regularisation strategies help overcome these errors with techniques that help your models handle noisy data and changing requirements. By learning to tweak training data and loss functions, and employ other regularisation approaches, you can ensure a model delivers excellent generalised performance and avoid overfitting errors.

DKK 430.00
1

Elliptic Curve Cryptography for Developers - Michael Rosing - Bog - Manning Publications - Plusbog.dk

React in Action - Mark Tielens Thomas - Bog - Manning Publications - Plusbog.dk

The Quick Python Book, Fourth Edition - Naomi Ceder - Bog - Manning Publications - Plusbog.dk

The Quick Python Book, Fourth Edition - Naomi Ceder - Bog - Manning Publications - Plusbog.dk

A fast-paced introduction to Python for intermediate developers–now with coverage of generative AI! For over 25 years, The Quick Python Book has been one of the best Python books money can buy. It concisely covers programming basics, while introducing Python''s comprehensive standard library and unique features in depth and detail. In this fourth edition, you''ll find new coverage of AI coding tools like Copilot and Google''s Colaboratory (Colab), and develop a mindset that can make the most of AI. The Quick Python Book, Fourth Edition includes: - - Python syntax, data structures, and best practices - - Python as an object oriented language - - Common Python libraries - - Basic data handling with Python - - Using AI code generation tools with Python - Whether you''re new to Python or looking to advance your basic skills, The Quick Python Book, Fourth Edition will get you writing effective Python code fast. Python authority and former Chair of the Python Software Foundation Board or Directors Naomi Ceder has returned to author this extensively revised fourth edition. With the personal touch of a skilled teacher, Naomi beautifully balances details of the language with the insights and advice you need to handle any task. About the technology: System automation. High-performance web apps. Cloud and back-end services. Cutting edge AI. No matter what you''re building, it pays to know how to read and write Python! The Quick Python Book has helped over 100,000 developers get up to speed with the Python programming language. This revised Fourth Edition, fully updated for Python 3.13, explores the latest features and libraries and shows you how to code smarter with AI tools like ChatGPT.

DKK 518.00
1

Build Your Own Robot - Marwan Alsabbagh - Bog - Manning Publications - Plusbog.dk

Grokking Data Structures - Marcello Rocca - Bog - Manning Publications - Plusbog.dk

Grokking Data Structures - Marcello Rocca - Bog - Manning Publications - Plusbog.dk

Don’t be perplexed by data structures! This fun, friendly, and fully illustrated guide makes it easy to learn useful data structures you''ll put to work every day. Grokking Data Structures makes it a breeze to learn the most useful day-to-day data structures. You''ll follow a steady learning path from absolute basics to advanced concepts, all illustrated with fun examples, engaging industry stories, and hundreds of graphics and cartoons. In Grokking Data Structures you''ll learn how to: - - Understand the most important and widely used data structures - - Identify use cases where data structures make the biggest difference - - Pick the best data structure solution for a coding challenge - - Understand the tradeoffs of data structures and avoid catastrophes - - Implement basic data collections like arrays, linked lists, stacks, and priority queues - - Use trees and binary search trees (BSTs) to organize data - - Use graphs to model relationships and learn about complex data - - Efficiently search by key using hash tables and hashing functions - - Reason about time and memory requirements of operations on data structures - Grokking Data Structures carefully guides you from the most basic data structures like arrays or linked lists all the way to powerful structures like graphs. It’s perfect for beginners, and you won''t need anything more than high school math to get started. Each data structure you encounter comes with its own complete Python implementation so you can start experimenting with what you learn right away. About the technology Data structures are vital for shaping and handling your data organization. They''re also an important part of most IT job interviews! Whether you''re new to data structures or just dusting off what you learned in school, this book will get you up to speed fast with no advanced math, abstract theory, or complicated proofs.

DKK 465.00
1

Geoprocessing with Python - Chris Garrad - Bog - Manning Publications - Plusbog.dk

Geoprocessing with Python - Chris Garrad - Bog - Manning Publications - Plusbog.dk

DESCRIPTION Geospatial data is hard to ignore. Nearly every car, phone, or camera has a GPS sensor, and aerial photos, satellite imagery, and data representing political boundaries, roads, rivers, and streams are available for free download from many websites. Geoprocessing is the science of reading, analyzing, and presenting geospatial data programmatically. The Python language, along with dozens of open source libraries and tools, makes it possible to take on professional geoprocessing tasks without investing in expensive proprietary packages like ArcGIS and MapInfo. Geoprocessing with Python teaches how to use the Python programming language along with free and open source tools to read, write, and process geospatial data. It shows how to access available data sets to make maps or perform analyses using free and open source tools like the GDAL, Shapely, and Fiona Python modules. Readers will master core practices like handling multiple vector file formats, editing and manipulating geometries, applying spatial and attribute filters, working with projections, and performing basic analyses on vector data. They’ll also learn how to create geospatial data, rather than just consuming it. The book also covers how to manipulate and analyze raster data, such as aerial photographs, satellite images, and digital elevation models. KEY SELLING POINTS Geoprocessing from the ground up Shows how to create custom geoprocessing tools Takes advantage of free and open source tools AUDIENCE Readers need a basic knowledge of Python or a similar programming language. No previous experience with geoprocessing or geospatial data required. Perfect for readers who have used Python with Esri ArcGIS and want to apply their Python skills elsewhere. ABOUT THE TECHNOLOGY Geoprocessing is the science of reading, analyzing, and presenting geospatial data programmatically. The Python language, along with dozens of open source libraries and tools, makes it possible to take on professional geoprocessing tasks without investing in expensive proprietary packages like ArcGIS and MapInfo.

DKK 406.00
1

Learn SQL in a Month of Lunches - Jeff Iannucci - Bog - Manning Publications - Plusbog.dk

Learn SQL in a Month of Lunches - Jeff Iannucci - Bog - Manning Publications - Plusbog.dk

Use SQL to get the data you need in no time at all! Learn to read and write basic queries, troubleshoot common problems, and control your own business data in just 24 short lessons–no programming experience required! In Learn SQL in a Month of Lunches you''ll master useful SQL skills like: - - Write your own SQL queries - - See only the data you need in large datasets - - Easily filter, sort, and cluster data - - Master basic data manipulation techniques - - Safely create, update, and delete data - Structured Query Language (SQL) is the standard way to get specific datasets out of large relational databases. If you use Excel, Tableau, or PowerBI to crunch business data, you''ve probably seen a lot of SQL already. And guess what? It''s easy to master the most useful parts of SQL! In just a few quick lessons, you can learn to write your own queries, modify existing SQL statements, and add a new superpower to your bag of tricks. Learn SQL in a Month of Lunches introduces you to the most useful parts of SQL for business data analysis. This practical book gives you instantly-useful techniques starting from the first short chapter. 25-year SQL veteran Jeff Iannucci makes SQL a snap through hands-on lab exercises, relevant code examples, and easy-to-understand language. About the technology For decades, Structured Query Language has been the standard way to talk to relational databases. Unlike many programming languages, SQL is easy to read and understand once you get the hang of it. You don''t need to be a data scientist—or even a tech professional—to master the most powerful features. For business data analysts, learning SQL empowers you to create better reports, uncover market insights, and freely explore large databases on your own.

DKK 485.00
1

Practical Probabilistic Programming - Ava Pfeffer - Bog - Manning Publications - Plusbog.dk

Practical Probabilistic Programming - Ava Pfeffer - Bog - Manning Publications - Plusbog.dk

DESCRIPTION Data accumulated about customers, products, and website users can not only help interpret the past, it can help predict the future! Probabilistic programming is a programming paradigm in which code models are used to draw probabilistic inferences from data. By applying specialized algorithms, programs assign degrees of probability to conclusions and make it possible to forecast future events like sales trends, computer system failures, experimental outcomes, and other critical concerns. Practical Probabilistic Programming explains how to use the PP paradigm to model application domains and express those probabilistic models in code. It shows how to use the Figaro language to build a spam filter and apply Bayesian and Markov networks to diagnose computer system data problems and recover digital images. Then it dives into the world of probabilistic inference, where algorithms help turn the extended prediction of social media usage into a science. The book covers functional-style programming for text analysis and using object-oriented models to predict social phenomena like the spread of tweets, and using open universe models to model real-life social media usage. It also teaches the principles of algorithms such as belief propagation and Markov chain Monte Carlo. The book closes out with modeling dynamic systems by using a product cycle as its main example and explains how probabilistic KEY SELLING POINTS Covers the basic rules of probabilistic inference Illustrated with useful practical examples Build a wide variety of probabilistic models AUDIENCE Code examples are written in Figaro. Some knowledge of Scala and a basic foundation in data science is helpful. No prior exposure to probabilistic programming is required. ABOUT THE TECHNOLOGY Probabilistic programming is a new discipline, and the tools and best practices are still emerging. Powerful new tools like the Figaro library built into Scala make probabilistic programming more practical in day-to-day work as a data scientist.

DKK 476.00
1

Linux in Action - David Clinton - Bog - Manning Publications - Plusbog.dk

Grokking Bitcoin - Kalle Rosenbaum - Bog - Manning Publications - Plusbog.dk

Fighting Churn with Data - Carl Gold - Bog - Manning Publications - Plusbog.dk

D3.js in Action, 2E - Elijah Meeks - Bog - Manning Publications - Plusbog.dk

CSS in Depth - Keith J Grant - Bog - Manning Publications - Plusbog.dk

HTTP/2 in Action - Barry Pollard - Bog - Manning Publications - Plusbog.dk

Quick Python Book, The - Naomi R Ceder - Bog - Manning Publications - Plusbog.dk

The Well-Grounded Rubyist - Joseph Leo - Bog - Manning Publications - Plusbog.dk

API Security in Action - Neil Madden - Bog - Manning Publications - Plusbog.dk

Natural Language Processing in Action - Hapke Hannes - Bog - Manning Publications - Plusbog.dk

Modern Java in Action - Raoul Gabriel Urma - Bog - Manning Publications - Plusbog.dk

Hello World! - Warren Sande - Bog - Manning Publications - Plusbog.dk