Python
Tadej Magajna
Flair is an easy-to-understand natural language processing (NLP) framework designed to facilitate training and distribution of state-of-the-art NLP models for named entity recognition, part-of-speech tagging, and text classification. Flair is also a text embedding library for combining different types of embeddings, such as document embeddings, Transformer embeddings, and the proposed Flair embeddings.Natural Language Processing with Flair takes a hands-on approach to explaining and solving real-world NLP problems. You'll begin by installing Flair and learning about the basic NLP concepts and terminology. You will explore Flair's extensive features, such as sequence tagging, text classification, and word embeddings, through practical exercises. As you advance, you will train your own sequence labeling and text classification models and learn how to use hyperparameter tuning in order to choose the right training parameters. You will learn about the idea behind one-shot and few-shot learning through a novel text classification technique TARS. Finally, you will solve several real-world NLP problems through hands-on exercises, as well as learn how to deploy Flair models to production.By the end of this Flair book, you'll have developed a thorough understanding of typical NLP problems and you’ll be able to solve them with Flair.
Cuantum Technologies LLC
Embark on a comprehensive journey to master natural language processing (NLP) with Python. Begin with foundational concepts like text preprocessing, tokenization, and key Python libraries such as NLTK, spaCy, and TextBlob. Explore the challenges of text data and gain hands-on experience in cleaning, tokenizing, and building basic NLP pipelines. Early chapters provide practical exercises to solidify your understanding of essential techniques.Advance to sophisticated topics like feature engineering using Bag of Words, TF-IDF, and embeddings like Word2Vec and BERT. Delve into language modeling with RNNs, syntax parsing, and sentiment analysis, learning to apply these techniques in real-world scenarios. Chapters on topic modeling and text summarization equip you to extract insights from data, while transformer-based models like BERT take your skills to the next level. Each concept is paired with Python-based examples, ensuring practical mastery.The final chapters focus on real-world projects, such as developing chatbots, sentiment analysis dashboards, and news aggregators. These hands-on applications challenge you to design, train, and deploy robust NLP solutions. With its structured approach and practical focus, this book equips you to confidently tackle real-world NLP challenges and innovate in the field.
Nirant Kasliwal
NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a work?ow for building NLP applications.We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn.We conclude by deploying these models as REST APIs with Flask.By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges.
Thushan Ganegedara
Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks.Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator.After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks.
Thushan Ganegedara, Andrei Lopatenko
Learning how to solve natural language processing (NLP) problems is an important skill to master due to the explosive growth of data combined with the demand for machine learning solutions in production. Natural Language Processing with TensorFlow, Second Edition, will teach you how to solve common real-world NLP problems with a variety of deep learning model architectures.The book starts by getting readers familiar with NLP and the basics of TensorFlow. Then, it gradually teaches you different facets of TensorFlow 2.x. In the following chapters, you then learn how to generate powerful word vectors, classify text, generate new text, and generate image captions, among other exciting use-cases of real-world NLP.TensorFlow has evolved to be an ecosystem that supports a machine learning workflow through ingesting and transforming data, building models, monitoring, and productionization. We will then read text directly from files and perform the required transformations through a TensorFlow data pipeline. We will also see how to use a versatile visualization tool known as TensorBoard to visualize our models.By the end of this NLP book, you will be comfortable with using TensorFlow to build deep learning models with many different architectures, and efficiently ingest data using TensorFlow Additionally, you’ll be able to confidently use TensorFlow throughout your machine learning workflow.
Nauka programowania. Rusz głową!
Eric Freeman
Przewodnik po kodowaniu i myśleniu komputacyjnym Programista to bardzo szczególny typ specjalisty. Jeśli uważasz, że myśli w inny sposób niż tak zwani normalni ludzie, to masz rację. Dobra wiadomość jest taka, że i Ty możesz się nauczyć myślenia komputacyjnego - umiejętności, która się przydaje niezależnie od charakteru rozwiązywanego problemu, środowiska czy języka programowania. Tylko w ten sposób można od początku nauki programowania pisać przejrzysty, uporządkowany, znakomity kod, zgodny z najlepszymi praktykami wypracowanymi przez mistrzów. Innymi słowy: pracować jak profesjonalny programista. Ta książka jest niezwykłym podręcznikiem programowania. Być może wygląda nieco dziwacznie, ale prędko się przekonasz, że to podręcznik jest wyjątkowo skuteczny: w końcu jego formuła została opracowana na podstawie najlepszych osiągnięć neurologii i kognitywistyki. W ten sposób Twój mózg się zaangażuje i błyskawicznie przyswoi sobie zasady programowania w Pythonie. Autor wykorzystał oczywistą prawdę, że najszybciej uczymy się wtedy, gdy uwzględnimy specyfikę działania własnego mózgu! Najpierw więc się zainteresujesz, potem zaangażujesz, wreszcie przygotujesz sobie warsztat pracy, czyli zainstalujesz Pythona. Później zaczniesz ćwiczyć myślenie komputacyjne i oczywiście napiszesz swój pierwszy program. A dalej będzie coraz ciekawiej... W tej książce między innymi: Istotne koncepcje programistyczne Zasady programowania w Pythonie Funkcje i rekurencja Programowanie obiektowe Tworzenie API dla aplikacji internetowych Widgety i zdarzenia Neurony płoną. Emocje szaleją. Tak napiszesz kod godny mistrza!
Nauka robotyki z językiem Python
Lentin Joseph
Roboty wkraczają do różnych dziedzin naszego życia, więc robotyka nabiera coraz większego znaczenia. Nauka o robotach, ich budowaniu i programowaniu jest dość złożoną, ale fascynującą dziedziną. Jej opanowanie wymaga wysiłku, jednak aby zaprojektować łatwy do wykorzystania interfejs, wystarczy posłużyć się kilkoma programami narzędziowymi oraz językiem Python. W ten sposób można zaprojektować zachowania robota, określić, w jaki sposób będzie zmierzał do celu, reagował na sygnały otaczającego świata, czy sprawić, by oczekiwał na instrukcje. Dzięki tej książce można się nauczyć, jak z wykorzystaniem języka Python oraz kilku popularnych frameworków stosowanych w robotyce, takich jak system ROS, budować autonomiczne roboty mobilne. Omówiono w niej również inne frameworki programistyczne, w tym również te dla Pythona. Aby równocześnie pokazać praktyczne wykorzystanie przedstawianego materiału, omówiono krok po kroku proces budowania robota-służącego ChefBot, który na przykład może podawać posiłki w domu, hotelu czy restauracji. W tej książce przedstawiono: zwięzłe podstawy robotyki i zasady projektowania oprogramowania robotów, aspekty projektowania CAD 2D i 3D z wykorzystaniem programów LibreCAD i Blender, budowanie modeli 3D z wykorzystaniem API Blender dla Pythona, zagadnienia sprzętowej warstwy projektowania robota, zasady obsługi sensorów robotów, w tym programowanie sensorów wizji, obsługę rozpoznawania mowy i syntezę mowy z wykorzystaniem Pythona i ROS, implementację sztucznej inteligencji za pomocą Pythona, zagadnienie testowania i kalibrowania robota. Przekonaj się, jak fascynujące jest programowanie robotów! Lentin Joseph — inżynier elektroniki, entuzjasta robotyki i ekspert w dziedzinie systemów wbudowanych. Szczególnie interesuje się robotyką, przetwarzaniem obrazu i zastosowaniem języka Python w programowaniu robotów. Jest również znawcą wielu platform oprogramowania robotów, takich jak system ROS (ang. Robot Operating system), V-REP i Actin. Biegle posługuje się bibliotekami przetwarzania obrazu, w tym OpenCV, OpenNI i PCL. Specjalizuje się również w dziedzinie projektowania 3D i programowania systemów wbudowanych na platformach Arduino i Launchpad Stellaris. Jest właścicielem firmy Qbotics Labs zajmującej się rozwijaniem robotyki i jej zastosowaniami w wielu dziedzinach.
Christian Adell, Jeffrey Kala, Karim Okasha
Network Automation Cookbook, now in its second edition, is your essential guide to building robust network automation workflows across modern hybrid infrastructures. Building on the foundation laid in the first edition, this version dives deeper into Ansible’s role in automating network infrastructure, expanding coverage to include modern use cases across enterprise and cloud networks.The book introduces Ansible’s core concepts, such as playbooks, inventories, variables, loops, and templates, and progresses to advanced topics such as parallelism, fact caching, custom filters, and modular design. You will automate real-world scenarios using Nokia SR, Cisco IOS, Juniper, and Arista devices in a fully reproducible virtual lab. The chapters also help you explore cloud automation for AWS, Azure, and Google Cloud, and integrate validation tools such as PyATS, Batfish, and Nautobot. New chapters cover event-driven automation, AWX for workflow execution, and Terraform integration. By using hands-on labs and fully reproducible recipes, you can practice real-world scenarios and reinforce your skills.By the end of this book, you’ll be well-equipped with the tools and workflows to automate infrastructure efficiently with Ansible.
Karim Okasha
Network Automation Cookbook is designed to help system administrators, network engineers, and infrastructure automation engineers to centrally manage switches, routers, and other devices in their organization's network. This book will help you gain hands-on experience in automating enterprise networks and take you through core network automation techniques using the latest version of Ansible and Python. With the help of practical recipes, you'll learn how to build a network infrastructure that can be easily managed and updated as it scales through a large number of devices. You'll also cover topics related to security automation and get to grips with essential techniques to maintain network robustness. As you make progress, the book will show you how to automate networks on public cloud providers such as AWS, Google Cloud Platform, and Azure. Finally, you will get up and running with Ansible 2.9 and discover troubleshooting techniques and network automation best practices. By the end of this book, you'll be able to use Ansible to automate modern network devices and integrate third-party tools such as NAPALM, NetBox, and Batfish easily to build robust network automation solutions.
Yoram Orzach, Deepanshu Khanna
With the increased demand for computer systems and the ever-evolving internet, network security now plays an even bigger role in securing IT infrastructures against attacks. Equipped with the knowledge of how to find vulnerabilities and infiltrate organizations through their networks, you’ll be able to think like a hacker and safeguard your organization’s network and networking devices. Network Protocols for Security Professionals will show you how.This comprehensive guide gradually increases in complexity, taking you from the basics to advanced concepts. Starting with the structure of data network protocols, devices, and breaches, you’ll become familiar with attacking tools and scripts that take advantage of these breaches. Once you’ve covered the basics, you’ll learn about attacks that target networks and network devices. Your learning journey will get more exciting as you perform eavesdropping, learn data analysis, and use behavior analysis for network forensics. As you progress, you’ll develop a thorough understanding of network protocols and how to use methods and tools you learned in the previous parts to attack and protect these protocols.By the end of this network security book, you’ll be well versed in network protocol security and security countermeasures to protect network protocols.
Edward L. Platt
NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use.If you’re a data scientist, engineer, or computational social scientist, this book will guide you in using the Python programming language to gain insights into real-world networks. Starting with the fundamentals, you’ll be introduced to the core concepts of network science, along with examples that use real-world data and Python code. This book will introduce you to theoretical concepts such as scale-free and small-world networks, centrality measures, and agent-based modeling. You’ll also be able to look for scale-free networks in real data and visualize a network using circular, directed, and shell layouts.By the end of this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems.
Manpreet Singh Ghotra, Rajdeep Dua
If you're aware of the buzz surrounding the terms such as machine learning, artificial intelligence, or deep learning, you might know what neural networks are. Ever wondered how they help in solving complex computational problem efficiently, or how to train efficient neural networks? This book will teach you just that.You will start by getting a quick overview of the popular TensorFlow library and how it is used to train different neural networks. You will get a thorough understanding of the fundamentals and basic math for neural networks and why TensorFlow is a popular choice Then, you will proceed to implement a simple feed forward neural network. Next you will master optimization techniques and algorithms for neural networks using TensorFlow. Further, you will learn to implement some more complex types of neural networks such as convolutional neural networks, recurrent neural networks, and Deep Belief Networks. In the course of the book, you will be working on real-world datasets to get a hands-on understanding of neural network programming. You will also get to train generative models and will learn the applications of autoencoders.By the end of this book, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle. While you are learning about various neural network implementations you will learn the underlying mathematics and linear algebra and how they map to the appropriate TensorFlow constructs.
V Kishore Ayyadevara
This book will take you from the basics of neural networks to advanced implementations of architectures using a recipe-based approach.We will learn about how neural networks work and the impact of various hyper parameters on a network's accuracy along with leveraging neural networks for structured and unstructured data.Later, we will learn how to classify and detect objects in images. We will also learn to use transfer learning for multiple applications, including a self-driving car using Convolutional Neural Networks.We will generate images while leveraging GANs and also by performing image encoding. Additionally, we will perform text analysis using word vector based techniques. Later, we will use Recurrent Neural Networks and LSTM to implement chatbot and Machine Translation systems.Finally, you will learn about transcribing images, audio, and generating captions and also use Deep Q-learning to build an agent that plays Space Invaders game.By the end of this book, you will have developed the skills to choose and customize multiple neural network architectures for various deep learning problems you might encounter.
Tomasz Rymarczyk Krzysztof Król
This publication was prepared as a permanent record of research findings presented by doctoral students and academics representing diverse research backgrounds and schools. The focus is on interdisciplinary solutions, combining engineering, computer science, and mathematical methods with approaches relevant to management science and socio-economic applications. The International Interdisciplinary PhD Workshop (IIPhDW) is a cyclical and international conference, and its primary function is to provide a platform for research presentations, knowledge exchange, and collaboration between young scientists from various disciplines. The 2025 edition featured a particularly strong technical component, encompassing artificial intelligence, computer science, automation and control, robotics and mechatronics, telecommunications, signal processing, as well as mechanical and production engineering. At the same time, the inclusion of topics in economics and management confirmed the workshop's broad scope and its ability to integrate research perspectives relevant to contemporary technological and organizational challenges. A significant group of publications includes works on process and biomedical tomography, as well as image reconstruction methods using machine learning and deep learning, including approaches combining physical models with neural network architectures. Examples include research on image reconstruction in electrical impedance tomography, the integration of tomography with neural networks for industrial process monitoring, and the use of ultrasound tomography in measurement and reconstruction analysis. This theme is further reinforced by works on hybrid tomography systems, process monitoring using mixed reality technology, and applications in the areas of physiological parameter monitoring and non-invasive diagnostics. The second recognizable axis is artificial intelligence in IT and cyberphysical systems, encompassing both the construction of predictive and classification models and their implementation in industrial, medical, and service environments. This trend includes work related to the application of machine learning methods in system and network security, solutions based on LLM agents in project team workflows, processing unstructured data using OCR and language models, and multimodal analysis in intelligent customer service systems. This perspective highlights the contemporary trend of convergence of AI techniques with data engineering, software engineering, and systems integration, which has direct implications for the design of scalable implementation solutions. The third thematic area covers embedded systems, communication, and signal processing, along with elements of computational resource optimization. The monograph includes papers on, among other things, phase shift estimation in noisy environments, pseudorandom sequence generation, acoustic feature detection, and the efficiency of machine learning applications at the network edge in the context of Kubernetes scheduling heuristics. In the monograph, this strand serves a methodological purpose, providing signal analysis tools and computational mechanisms that form the foundation for many AI and measurement system applications. A significant complement to the technical perspective are works in the areas of management and organizational and economic analysis, which address the need to understand the determinants of technology implementation and the conduct of innovative projects. The publications address, among other things, the predictors of success in startup management and the analysis of organizational improvements in public institutions. Their presence strengthens the interdisciplinary nature of the monograph by demonstrating that the effectiveness of engineering solutions depends not only on the quality of algorithms and devices, but also on the organizational, process, and decision-making context. The monograph is intended as a reference for academics and doctoral students, particularly those seeking examples of research that combines theory with application. The collected papers offer a comprehensive overview of research activities typical of early careers in science, from conceptual studies and method analysis, through device and software architecture prototyping, to experiments and evaluation of the effectiveness of proposed solutions. At the same time, the publication allows for the identification of common methodological denominators, such as the growing importance of measurement data, simulation, deep learning, systems integration, and the pursuit of real-time operation in industrial and biomedical environments. The introduction, on the one hand, contextualizes the monograph within the mission of IIPhDW as a workshop supporting researcher development and the internationalization of research. On the other hand, it organizes the chapter topics in the perspective of dominant technological trends and application needs that permeate various fields. Consequently, the monograph can be viewed as a synthetic overview of current research directions for doctoral students and young academics, as well as an inspiration for undertaking work combining artificial intelligence methods, measurement systems, software engineering, and management analyses within modern interdisciplinary projects.
Bethany Griggs
A key technology for building web applications and tooling, Node.js brings JavaScript to the server enabling full-stack development in a common language. This fourth edition of the Node Cookbook is updated with the latest Node.js features and the evolution of the Node.js framework ecosystems.This practical guide will help you to get started with creating, debugging, and deploying your Node.js applications and cover solutions to common problems, along with tips to avoid pitfalls. You'll become familiar with the Node.js development model by learning how to handle files and build simple web applications and then explore established and emerging Node.js web frameworks such as Express.js and Fastify. As you advance, you'll discover techniques for detecting problems in your applications, handling security concerns, and deploying your applications to the cloud. This recipe-based guide will help you to easily navigate through various core topics of server-side web application development with Node.js.By the end of this Node book, you'll be well-versed with core Node.js concepts and have gained the knowledge to start building performant and scalable Node.js applications.
Nowoczesna analiza danych w Excelu. Power Query, Power Pivot i inne narzędzia
George Mount
Organizacje stosują zaawansowane narzędzia i techniki, aby umożliwić podejmowanie decyzji na podstawie danych. Jeszcze do niedawna MS Excel nie był w stanie sprostać wymaganiom analityków, obecnie jest wschodzącą gwiazdą w świecie nowoczesnej analizy danych. Kluczem do sukcesu stało się opanowanie takich narzędzi jak Power Pivot czy Power Query. Dzięki tej praktycznej książce przekonasz się, że w Excelu możesz przeprowadzić dogłębną analizę danych i wyciągnąć z nich cenną wiedzę. Wystarczy, że skorzystasz z najnowszych funkcji i narzędzi Excela. W poradniku pokazano, jak za pomocą Power Query budować przepływy pracy porządkujące dane i jak projektować w skoroszycie relacyjne modele danych przy użyciu Power Pivot. Ponadto odkryjesz nowe możliwości przeprowadzania analiz, w tym dynamiczne funkcje tablicowe i pozyskiwanie wartościowych informacji z wykorzystaniem sztucznej inteligencji. Dowiesz się również, jak za sprawą integracji z Pythonem zautomatyzować analizę danych i budować raporty. W książce: tworzenie procesów porządkujących dane w Excelu za pomocą Power Query relacyjne modele danych i wskaźniki analityczne w Power Pivot korzystanie z dynamicznych funkcji tablicowych zastosowanie AI do identyfikacji wzorców i trendów w danych integracja funkcjonalności Pythona z Excelem Książka jest łatwa w odbiorze, praktyczna i pomocna dla analityków, a także zwykłych użytkowników! Meghan Finley, autorka i redaktorka tekstów technicznych
Nowoczesne analizy biznesowe. Zwiększanie wartości danych przy użyciu Pythona i R
Deanne Larson
"Lektura obowiązkowa dla wszystkich analityków biznesowych i danetyków." Balaji Dhamodharan, światowy lider w dziedzinie danetyki, NXP Semiconductors "Ta książka to niezastąpione źródło wiedzy dla każdego, kto pragnie opanować szybko zmieniający się świat analityki." Lipi Deepaakshi Patnaik, starszy inżynier oprogramowania, Zeta Wydobycie wartości biznesowej z ogromu danych to trudny i wymagający proces. Przekształcenie surowych danych w użyteczne informacje wymaga od analityka biegłego posługiwania się wieloma technologiami, takimi jak bazy danych, narzędzia programistyczne czy komercyjne narzędzia analityczne. Ten praktyczny przewodnik pokazuje programistom rozumiejącym koncepcje analizy, jak rozwijać umiejętności niezbędne do uzyskania wartości biznesowej. Autorka, zajmująca się danetyką zarówno od strony praktycznej, jak i naukowej, pomaga połączyć światy biznesu i techniki, aby spełnić te wymagania. Rozwiń umiejętności posługiwania się językami R i Python na z życia wziętych przykładach. Dowiedz się również, jak wykorzystywać właściwe metodologie w celu skutecznego realizowania celów. Metodyka uczenia się połączona z narzędziami open source jest kluczem do dostarczania rzeczywistych wartości biznesowych. Książka ta pokazuje, jak: - Stosować metodologie analityki biznesowej, aby osiągnąć pomyślne wyniki - Czyścić i przekształcać dane przy użyciu R i Pythona - Używać R i Pythona do wykonywania eksploracyjnej analizy danych - Tworzyć modele predykcyjne do rozwiązywania problemów biznesowych w R i Pythonie - Używać Pythona, R i narzędzi analitycznych do obsługi wielkich wolumenów danych - Współpracować z inżynierami danych i danetykami - Mierzyć skuteczność analiz biznesowych Dr. Deanne Larson jest eksperktą w dziedzinie danetyki oraz edukatorką, która pomaga największym firmom odblokować wartości biznesowe dzięki analityce. Dzięki wykładom w zakresie analiz, sztucznej inteligencji i przywództwa prowadzonym na takich uczelniach, jak MIT, Harvard, Stanford i NYU, stała się poszukiwanym wykładowcą i oddanym mentorem swojej dziedziny.
Sylwester Walczak
Książka Sylwestra Walczaka jest poświęcona Django, wolnej, otwartoźródłowej platformie programistycznej służącej do tworzenia aplikacji internetowych. Autor udowadnia, że wbrew obiegowym opiniom Django jako framework nadaje się do budowy mikroserwisów - autonomicznych usług, które współpracują ze sobą, tworząc na przykład serwis internetowy. Odwołuje się przy tym do API potrzebnego do obsługi kawiarni. Jest to więc swojego rodzaju instrukcja, która przeprowadza przez projektowanie, programowanie i wdrożenie systemu do obsługi kawiarni, składającego się między innymi z takich aplikacji jak magazyn, menu, obsługa klientów i kolejkowanie utworzonych zamówień. To podręcznik przeznaczony dla programistów; do zrozumienia poruszonych w nim zagadnień wymagana jest znajomość języka Python i komunikacji webowej. Lektura kolejnych rozdziałów pozwoli Ci na tworzenie bibliotek i napisanie wtyczki do Django, odpowiadającej za autoryzację. Poznasz świat mikrousług, w tym ich zalety i wady. Przy okazji zapoznasz się z kilkoma narzędziami przydatnymi nie tylko w świecie architektury rozproszonej. Zatem - kawa i do dzieła? Dzięki książce: Dowiesz się, co to jest konteneryzacja, Docker, REST API i webhooki Utworzysz własny system autoryzacji Napiszesz system rozproszony Dynamicznie przepiszesz serializery do widoków Przygotujesz dokumentację API Opracujesz komunikację między usługami
Pratap Dangeti, Allen Yu, Claire Chung, Aldrin...
Data mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining.You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models.By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional.This Learning Path includes content from the following Packt products:• Statistics for Machine Learning by Pratap Dangeti• Matplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin Yim• Pandas Cookbook by Theodore Petrou
Mantavya Gajjar
Odoo is a Python-based ERP system and is completely open source. Odoo is a comprehensive suite of business applications offering a wealth of functionalities that can be deployed to meet your business needs.This book will help you manage the different functionalities of your business and optimize it. You will learn in detail about the various facets of the business process such as sales, accounting, purchases, manufacturing, and inventory. We will cover each of these topics in detail and learn how Odoo handles all these tasks with much ease. With its modular approach, you will be able to build customized solutions, take advantage of the Odoo 10 system in your organization, and master basic administration. We will cover modules and applications in Odoo that will help optimize quality checks. You will also be able to customize major reporting functions for your teams and set up forms and documents for sales, purchase, inventory, and so on. By the end of the book, you will be able to use the major functionalities of Odoo 10 and fully implement them into your business.
Alexandre Fayolle, Holger Brunn
Odoo is a full-featured open source ERP with a focus on extensibility. The flexibility and sustainability of open source are also a key selling point of Odoo. It is built on a powerful framework for rapid application development, both for back-end applications and front-end websites. Version 11 offers better usability and speed: a new design (as compared to the current Odoo Enterprise version) and a mobile interface.The book starts by covering Odoo installation and administration and Odoo Server deployment. It then delves into the implementation of Odoo modules, the different inheritance models available in Odoo. You will then learn how to define access rules for your data; how to make your application available in different languages; how to expose your data models to end users on the back end and on the front end; and how to create beautiful PDF versions of your data. By the end of the book, you will have a thorough knowledge of Odoo and will be able to build effective applications by applying Odoo development best practices
Parth Gajjar, Alexandre Fayolle, Holger Brunn, Daniel...
Odoo is a powerful framework known for rapid application development. Its latest release, Odoo 12, introduces tons of new features. With this book, you’ll learn how to develop powerful Odoo applications from scratch, using all the latest features.This Odoo cookbook starts by covering Odoo installation and deployment on the server. Next, you’ll explore the Odoo framework with real-world examples. You’ll create a new Odoo module from the ground up and progress to advanced framework concepts. You’ll also learn how to modify existing applications, including Point of Sale (POS). This book is not just limited to backend development; the advanced JavaScript recipes for creating new views and widgets will help you build beautiful UI elements. As you move forward, you’ll gain insights into website development and become a quality Odoo developer by studying performance optimization, debugging, and automated tests. Finally, you’ll learn the latest concepts like multi-website, In-App Purchasing (IAP), Odoo.sh, and IoT Box.By the end of the book, you’ll have all the knowledge you need to build powerful Odoo applications. The development best practices used in this book will undoubtedly come handy when you are working with the Odoo framework.
Parth Gajjar, Alexandre Fayolle, Holger Brunn, Daniel...
With its latest iteration, the powerful Odoo framework released a wide variety of features for rapid application development. This updated Odoo development cookbook will help you explore the new features in Odoo 14 and learn how to use them to develop Odoo applications from scratch. You'll learn about the new website concepts in Odoo 14 and get a glimpse of Odoo's new web-client framework, the Odoo Web Library (OWL).Once you've completed the installation, you'll begin to explore the Odoo framework with real-world examples. You'll then create a new Odoo module from the ground up and progress to advanced framework concepts. You'll also learn how to modify existing applications, including Point of Sale (POS) applications. This book isn't just limited to backend development; you'll discover advanced JavaScript recipes for creating new views and widgets. As you progress, you'll learn about website development and become a quality Odoo developer by studying performance optimization, debugging, and automated testing. Finally, you'll delve into advanced concepts such as multi-website, In-App Purchasing (IAP), Odoo.sh, the IoT Box, and security.By the end of the book, you'll have all the knowledge you need to build impressive Odoo applications and you'll be well versed in development best practices that will come in handy when working with the Odoo framework.
Husen Daudi, Jay Vora, Parth Gajjar, Alexandre...
The latest version of the powerful Odoo framework uncovers a wide variety of features for rapid application development. Written by seasoned Odoo experts, this updated Odoo Development Cookbook will help you explore Odoo 17’s new features and use them to develop applications from scratch.You'll learn about website development concepts and get to grips with the Odoo Web Library (OWL), as well as create a new Odoo module from the ground up before progressing to advanced framework concepts. The book also shows you how to modify existing applications, including Point of Sale (POS) applications. Going beyond backend development, you'll discover advanced JavaScript recipes for creating new views and widgets. You'll get a clear understanding of website development and be on your way to becoming a proficient Odoo developer by studying performance optimization, debugging, and automated testing.By the end of this book, you'll have the knowledge you need to build impressive applications and be well-versed in Odoo development best practices.