10 Machine Learning Blueprints You Should Know for Cybersecurity. Protect your systems and boost your defenses with cutting-edge AI techniques

Rajvardhan Oak

Machine learning in security is harder than other domains because of the changing nature and abilities of adversaries, high stakes, and a lack of ground-truth data. This book will prepare machine learning practitioners to effectively handle tasks in the challenging yet exciting cybersecurity space.The book begins by helping you understand how advanced ML algorithms work and shows you practical examples of how they can be applied to security-specific problems with Python – by using open source datasets or instructing you to create your own. In one exercise, you’ll also use GPT 3.5, the secret sauce behind ChatGPT, to generate an artificial dataset of fabricated news. Later, you’ll find out how to apply the expert knowledge and human-in-the-loop decision-making that is necessary in the cybersecurity space. This book is designed to address the lack of proper resources available for individuals interested in transitioning into a data scientist role in cybersecurity. It concludes with case studies, interview questions, and blueprints for four projects that you can use to enhance your portfolio.By the end of this book, you’ll be able to apply machine learning algorithms to detect malware, fake news, deep fakes, and more, along with implementing privacy-preserving machine learning techniques such as differentially private ML.

3D Deep Learning with Python. Design and develop your computer vision model with 3D data using PyTorch3D and more

Xudong Ma, Vishakh Hegde, Lilit Yolyan

With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time.Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You’ll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you’ll realize how coding for these deep learning models becomes easier using the PyTorch3D library.By the end of this deep learning book, you’ll be ready to implement your own 3D deep learning models confidently.

Accelerate Deep Learning Workloads with Amazon SageMaker. Train, deploy, and scale deep learning models effectively using Amazon SageMaker

Vadim Dabravolski

Over the past 10 years, deep learning has grown from being an academic research field to seeing wide-scale adoption across multiple industries. Deep learning models demonstrate excellent results on a wide range of practical tasks, underpinning emerging fields such as virtual assistants, autonomous driving, and robotics. In this book, you will learn about the practical aspects of designing, building, and optimizing deep learning workloads on Amazon SageMaker. The book also provides end-to-end implementation examples for popular deep-learning tasks, such as computer vision and natural language processing. You will begin by exploring key Amazon SageMaker capabilities in the context of deep learning. Then, you will explore in detail the theoretical and practical aspects of training and hosting your deep learning models on Amazon SageMaker. You will learn how to train and serve deep learning models using popular open-source frameworks and understand the hardware and software options available for you on Amazon SageMaker. The book also covers various optimizations technique to improve the performance and cost characteristics of your deep learning workloads.By the end of this book, you will be fluent in the software and hardware aspects of running deep learning workloads using Amazon SageMaker.

AI - podejście pragmatyczne

Noah Gift

Opanuj skuteczne, gotowe do użycia rozwiązania biznesowe dla sztucznej inteligencji i uczenia maszynowego AI podejście pragmatyczne pomaga rozwiązywać praktyczne problemy przy użyciu nowoczesnego uczenia maszynowego, sztucznej inteligencji i chmurowych narzędzi obliczeniowych. Noah Gift demistyfikuje wszelkie koncepcje i narzędzia potrzebne do osiągnięcia wyników nawet jeśli Czytelnik nie ma solidnego przygotowania z matematyki lub data science. Autor wyjaśnia skuteczne, gotowe do użycia rozwiązania udostępniane przez Amazon, Google i Microsoft oraz demonstruje sprawdzone techniki wykorzystujące ekosystem analizy danych oparty na języku Python. Proponowane podejścia i przykłady pomagają ukierunkować i uprościć każdy krok od wdrożenia po produkcję i budować rozwiązania o niezwykłych możliwościach skalowania. W miarę poznawania działania rozwiązań Machine Language (ML) będziesz uzyskiwać coraz bardziej intuicyjne zrozumienie tego, co można dzięki nim osiągnąć i jak zmaksymalizować ich wartość. Na tych podstawach autor krok po kroku prezentuje budowanie chmurowych aplikacji AI/ML do rozwiązywania realistycznych problemów w dziedzinie marketingu, zarządzania projektami, wyceniania produktów, nieruchomości i dużo więcej. Bez względu na to, czy jesteś profesjonalistą biznesowym, osobą decyzyjną, studentem czy programistą, eksperckie wskazówki autora i rozbudowane analizy przypadków przygotują cię do rozwiązywania problemów data science w niemal dowolnym środowisku. Uzyskaj i skonfiguruj wszystkie potrzebne narzędzia Szybko przejrzyj wszystkie funkcjonalności Pythona, których potrzebujesz do budowania aplikacji uczenia maszynowego Opanuj narzędzia AI i ML oraz cykl życia projektu Korzystaj z narzędzi analitycznych Pythona, takich jak IPython, Pandas, Numpy, Juypter Notebook i Sklearn Dołącz pragmatyczną pętlę zwrotną, która pozwoli nieustannie poprawiać wydajność naszych procedur i systemów Projektuj chmurowe rozwiązania AI oparte na Google Cloud Platform, uwzględniając usługi TPU, Colaboratory i Datalab Definiuj chmurowe przepływy pracy w Amazon Web Services, w tym wystąpienia punktowe, potoki kodu i inne Pracuj z API sztucznej inteligencji w Microsoft Azure Poznaj budowanie sześciu rzeczywistych aplikacji AI od początku do końca

AI Crash Course. A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python

Hadelin de Ponteves

Welcome to the Robot World … and start building intelligent software now!Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch.AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination.

AI for Absolute Beginners: A Clear Guide to Tomorrow. Demystifying AI for Beginners and Paving the Path to Future Innovations

Oliver Theobald

The course begins with an engaging introduction to the world of Artificial Intelligence, making it approachable for absolute beginners. We unravel the mysteries of AI's evolution, from its historical roots to the cutting-edge technologies shaping our future. By explaining complex concepts in simple terms, this course aims to illuminate the path for those curious about how AI impacts our world.The course focuses on the core components of AI, including machine learning, deep learning, and natural language processing, before advancing to more specialized topics like generative AI and computer vision. Each module is designed to build a comprehensive understanding, emphasizing why these technologies are crucial for solving real-world problems and how they're transforming industries.The course wraps up by exploring the ethical considerations and privacy concerns associated with AI, along with a visionary look at the future of work in an AI-driven world. It offers a treasure trove of further resources, ensuring learners have everything they need to continue their exploration of AI.

AI w biznesie. Jak zarabiać więcej dzięki sztucznej inteligencji

Mirosław Skwarek

Biznesowa rewolucja na miarę internetu. Już tu jest! Pojęcie sztucznej inteligencji (SI, ang. AI) używane jest od lat pięćdziesiątych XX wieku. Jednak dopiero niedawno stało się gorącym, odmienianym przez wszystkie przypadki i możliwości terminem, który działa na wyobraźnię ludzi na całym świecie. Sprawcą zamieszania jest ChatGPT - chatbot opracowany przez firmę OpenIA, który służy do generowania odpowiedzi na dane wprowadzone przez użytkownika. Innymi słowy: super mózg z dostępem do wszystkich zasobów internetu pomyślany tak, by dzielić się nimi z człowiekiem w sposób, jakiego ten człowiek akurat sobie życzy. Możliwości ChataGPT są imponujące. Całą wiedzę, jaką zgromadziliśmy, mamy za jego pośrednictwem na wyciągnięcie ręki, dostępną w kilka sekund. Dysponuje także naszym doświadczeniem i umiejętnościami - zdolnością do researchu, umiejętnościami obliczeniowymi, kreatywnością na poziomie profesjonalnego copywritera. Analizuje i wyciąga wnioski, planuje, tłumaczy zagraniczne teksty, tworzy pisma, odpowiedzi na zapytania, oferty, wpisy na bloga i do mediów społecznościowych. Brzmi jak science fiction? Może. Jednak ChatGPT już tu jest i czeka, aż go zatrudnisz w swojej firmie i pozwolisz mu robić dla Ciebie rzeczy, które zrobić trzeba, a na których zrobienie nie masz czasu, chęci, albo pieniędzy - bo realizację niektórych zadań trzeba byłoby powierzyć zleceniobiorcy. Tymczasem elektroniczny super mózg zrobi je dla Ciebie za darmo. Ta książka podpowie Ci jak namówić Chata GPT, by dla Ciebie pracował.   Przedsiębiorca, marketingowiec, edukator oraz autor bestsellerów. Posłuchaj, co o swojej najnowszej książce mówi jej twórca – Mirosław Skwarek ⤵️

AI. Наддержави штучного інтелекту

Кай Фу Лі

Чесно про те, кому загрожує втрата роботи через штучний інтелект та які економічні наслідки тягнуть за собою технологічні прориви. Що буде з людиною, коли штучний інтелект робитиме геть усе? Штучний інтелект змінює світ. Чи буде суперкомпютер правити світом? Що ми можемо зробити для того, щоб не лишитися позаду прогресу?

Analityka biznesowa wspomagana sztuczną inteligencją. Ulepszanie prognoz i podejmowania decyzji za pomocą uczenia maszynowego

Tobias Zwingman

Wykorzystaj analizy biznesowe i sztuczną inteligencję, aby napędzać rozwój przedsiębiorstwa, podnosić wydajność i ulepszać podejmowanie decyzji biznesowych. Dzięki tej praktycznej książce z rzeczywistymi przykładami wykorzystującymi Power BI można poznać najbardziej odpowiednie przypadki użycia AI w rozwiązaniach BI, w tym ulepszone prognozowanie, zautomatyzowaną klasyfikację i zalecenia wspomagane przez AI. Ponadto nauczysz się, jak wydobywać spostrzeżenia z niestrukturalnych źródeł danych, takich jak dokumenty tekstowe lub pliki obrazów. Tobias Zwingmann pomaga profesjonalistom BI, analitykom biznesowym i specjalistom od danych rozpoznać obszary, w których sztuczna inteligencja ma szczególnie istotny wpływ. Dowiedz się, jak wykorzystać popularne platformy AI jako usługi oraz AutoML, aby tworzyć dowody koncepcji klasy korporacyjnej bez pomocy inżynierów oprogramowania lub danetyków. •  Wykorzystaj AI, aby napędzać wpływ na biznes w środowiskach BI •  Używaj AutoML do automatycznego klasyfikowania i lepszego prognozowania •  Wdrażaj usługi rekomendacji jako pomoc w podejmowaniu decyzji •  Wydobywaj spostrzeżenia z wielkoskalowych danych tekstowych za pomocą przetwarzania języka naturalnego •  Wyodrębniaj informacje z dokumentów i obrazów, wykorzystując widzenie komputerowe •  Buduj interaktywne interfejsy użytkownika dla tablic kontrolnych wspomaganych przez AI •  Implementuj kompletne studia przypadków w celu budowania tablic analitycznych zasilanych przez AI   „Po 15 latach spędzonych w świecie danych książka ta wywróciła do góry nogami mój ogląd klasycznego rozwiązania BI. Jest doskonale zaprojektowana i skonstruowana. Szkoda, że nie miałem takiej książki dużo wcześniej.” —Kai Aschenbach Szef działu narzędzi BI, HDI Global SE „Analityka biznesowa wspomagana sztuczną inteligencją to książka niezbędna dla każdego, kto chce zrozumieć, jak można usprawnić analizy biznesowe za pomocą AI.” —Ram Kumar Główny specjalista d/s danych i analityki, Cigna Tobias Zwingmann jest doświadczonym danetykiem z solidnymi podstawami biznesowymi. Jest współtwórcą niemieckiego startupu RAPYD.AI, którego misją jest pomoc w adaptowaniu uczenia maszynowego i sztucznej inteligencji przez firmy z szybszym uzyskiwaniem korzyści biznesowych.

Android: Game Programming. A Developer's Guide

Raul Portales, John Horton

Gaming has historically been a strong driver of technology, whether we’re talking about hardware or software performance, the variety of input methods, or graphics support and the Android game platform is no different. Android is a mature, yet still growing, platform that many game developers have embraced as it provides tools, APIs, and services to help bootstrap Android projects and ensure their success, many of which are specially designed to help game developers.Since Android uses one of the most popular programming languages, Java, as the primary language to build apps of all types, you will start this course by first obtaining a solid grasp of the Java language and its foundation APIs. This will improve your chances of succeeding as an Android app developer. We will show you how to get your Android development environment set up and you will soon have your first working game.The course covers all the aspects of game development through various engrossing and insightful game projects. You will learn all about frame-by-frame animations and resource animations using a space shooter game, create beautiful and responsive menus and dialogs, and explore the different options to play sound effects and music in Android. You will also learn the basics of creating a particle system and will see how to use the Leonids library. By the end of the course, you will be able to configure and use Google Play Services on the developer console and port your game to the big screen.This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:? Learning Java by Building Android Games by John Horton? Android Game Programming by Example by John Horton? Mastering Android Game Development by Raul Portales

Applied Machine Learning Explainability Techniques. Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more

Aditya Bhattacharya

Explainable AI (XAI) is an emerging field that brings artificial intelligence (AI) closer to non-technical end users. XAI makes machine learning (ML) models transparent and trustworthy along with promoting AI adoption for industrial and research use cases.Applied Machine Learning Explainability Techniques comes with a unique blend of industrial and academic research perspectives to help you acquire practical XAI skills. You'll begin by gaining a conceptual understanding of XAI and why it's so important in AI. Next, you'll get the practical experience needed to utilize XAI in AI/ML problem-solving processes using state-of-the-art methods and frameworks. Finally, you'll get the essential guidelines needed to take your XAI journey to the next level and bridge the existing gaps between AI and end users.By the end of this ML book, you'll be equipped with best practices in the AI/ML life cycle and will be able to implement XAI methods and approaches using Python to solve industrial problems, successfully addressing key pain points encountered.

Applied Machine Learning for Healthcare and Life Sciences Using AWS. Transformational AI implementations for biotech, clinical, and healthcare organizations

Ujjwal Ratan

While machine learning is not new, it's only now that we are beginning to uncover its true potential in the healthcare and life sciences industry. The availability of real-world datasets and access to better compute resources have helped researchers invent applications that utilize known AI techniques in every segment of this industry, such as providers, payers, drug discovery, and genomics.This book starts by summarizing the introductory concepts of machine learning and AWS machine learning services. You’ll then go through chapters dedicated to each segment of the healthcare and life sciences industry. Each of these chapters has three key purposes -- First, to introduce each segment of the industry, its challenges, and the applications of machine learning relevant to that segment. Second, to help you get to grips with the features of the services available in the AWS machine learning stack like Amazon SageMaker and Amazon Comprehend Medical. Third, to enable you to apply your new skills to create an ML-driven solution to solve problems particular to that segment. The concluding chapters outline future industry trends and applications.By the end of this book, you’ll be aware of key challenges faced in applying AI to healthcare and life sciences industry and learn how to address those challenges with confidence.

Architecting AI Solutions on Salesforce. Design powerful and accurate AI-driven state-of-the-art solutions tailor-made for modern business demands

Lars Malmqvist

Written for Salesforce architects who want quickly implementable AI solutions for their business challenges, Architecting AI Solutions on Salesforce is a shortcut to understanding Salesforce Einstein’s full capabilities – and using them.To illustrate the full technical benefits of Salesforce’s own AI solutions and components, this book will take you through a case study of a fictional company beginning to adopt AI in its Salesforce ecosystem. As you progress, you'll learn how to configure and extend the out-of-the-box features on various Salesforce clouds, their pros, cons, and limitations. You'll also discover how to extend these features using on- and off-platform choices and how to make the best architectural choices when designing custom solutions. Later, you'll advance to integrating third-party AI services such as the Google Translation API, Microsoft Cognitive Services, and Amazon SageMaker on top of your existing solutions. This isn’t a beginners’ Salesforce book, but a comprehensive overview with practical examples that will also take you through key architectural decisions and trade-offs that may impact the design choices you make.By the end of this book, you'll be able to use Salesforce to design powerful tailor-made solutions for your customers with confidence.

Augmented Reality for Android Application Development. As an Android developer, including Augmented Reality (AR) in your mobile apps could be a profitable new string to your bow. This tutorial takes you through every aspect of AR for Android with lots of hands-on exercises

Dr. Raphael Grasset, Jens Grubert

Augmented Reality offers the magical effect of blending the physical world with the virtual world, which brings applications from your screen into your hands. AR redefines advertising and gaming, as well as education. It will soon become a technology that will have to be mastered as a necessity by mobile application developers.Augmented Reality for Android Application Development enables you to implement sensor-based and computer vision-based AR applications on Android devices. You will learn about the theoretical foundations and practical details of implemented AR applications, and you will be provided with hands-on examples that will enable you to quickly develop and deploy novel AR applications on your own.Augmented Reality for Android Application Development will help you learn the basics of developing mobile AR browsers, how to integrate and animate 3D objects easily with the JMonkeyEngine, how to unleash the power of computer vision-based AR using the Vuforia AR SDK, and will teach you about popular interaction metaphors. You will get comprehensive knowledge of how to implement a wide variety of AR apps using hands-on examples.This book will make you aware of how to use the AR engine, Android layout, and overlays, and how to use ARToolkit. Finally, you will be able to apply this knowledge to make a stunning AR application.

Badanie i zarządzanie ryzykiem w transporcie drogowym z zastosowaniem algorytmów sztucznej inteligencji

Mariusz Izdebski

Praca dotyczy tematyki zarządzania ryzykiem w transporcie drogowym z wykorzystaniem algorytmów sztucznej inteligencji w procesach przewozowych do minimalizacji zdarzeń niebezpiecznych. Wartością poznawczą przeprowadzonych badań jest opracowanie autorskich, oryginalnych modeli zarządzania ryzykiem w transporcie drogowym wraz z ich algorytmizacją narzędziami sztucznej inteligencji. Opracowane modele zarządzania ryzykiem mogą mieć zastosowanie w różnych obszarach, np. budownictwie. Wykorzystanie algorytmów sztucznej inteligencji w zarządzaniu ryzykiem w transporcie drogowym pozwoliło na opracowanie oryginalnych metod oceny i zarządzania ryzykiem w procesach przewozowych. Do badania redukcji poziomu ryzyka zastosowano dwa zaawansowane algorytmy sztucznej inteligencji - mrówkowy i genetyczny. Sposób ich działania jest różny, co pozwoliło na porównanie jakości generowanych rozwiązań, a tym samym wyznaczenie efektywności tych algorytmów w zarządzaniu ryzykiem w transporcie drogowym. Monografia składa się z dziewięciu rozdziałów, które podzielono na trzy obszary tematyczne. W pierwszym obszarze (rozdz. 1-3) zdefiniowano najnowsze badania z zakresu tematyki ryzyka w transporcie drogowym, scharakteryzowano kluczowe zagrożenia w procesach przewozowych i przedstawiono procedurę zarządzania ryzykiem w transporcie drogowym. Kluczowym elementem tej części monografii jest opis algorytmów sztucznej inteligencji stosowanych w zarządzaniu ryzykiem w transporcie drogowym, ze szczególnym podkreśleniem dużej roli, jaką odgrywają użyte algorytmy. W drugim obszarze (rozdz. 4 i 5) opisano modele zarządzania ryzykiem w transporcie drogowym i przedstawiono ich formalny zapis. W trzecim obszarze (rozdz. 6-8) opisano proces algorytmizacji opracowanych modeli zarządzania ryzykiem wraz ze sposobem szacowania ryzyka na odcinkach sieci transportowej i przedstawiono weryfikację algorytmów zastosowanych w aplikacji do przykładów. W podsumowaniu monografii przedłożono rekomendacje dla decydentów zarządzających ryzykiem w transporcie drogowym, a także podkreślono oryginalność przedstawionych badań i ich dalszy kierunek.

Building Data Science Applications with FastAPI. Develop, manage, and deploy efficient machine learning applications with Python - Second Edition

François Voron

Building Data Science Applications with FastAPI is the go-to resource for creating efficient and dependable data science API backends. This second edition incorporates the latest Python and FastAPI advancements, along with two new AI projects – a real-time object detection system and a text-to-image generation platform using Stable Diffusion. The book starts with the basics of FastAPI and modern Python programming. You'll grasp FastAPI's robust dependency injection system, which facilitates seamless database communication, authentication implementation, and ML model integration. As you progress, you'll learn testing and deployment best practices, guaranteeing high-quality, resilient applications. Throughout the book, you'll build data science applications using FastAPI with the help of projects covering common AI use cases, such as object detection and text-to-image generation. These hands-on experiences will deepen your understanding of using FastAPI in real-world scenarios. By the end of this book, you'll be well equipped to maintain, design, and monitor applications to meet the highest programming standards using FastAPI, empowering you to create fast and reliable data science API backends with ease while keeping up with the latest advancements.

Building Data-Driven Applications with LlamaIndex. A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Andrei Gheorghiu

Generative AI, such as Large Language Models (LLMs) possess immense potential. These models simplify problems but have limitations, including contextual memory constraints, prompt size issues, real-time data gaps, and occasional hallucinations.With this book, you’ll go from preparing the environment to gradually adding features and deploying the final project. You’ll gradually progress from fundamental LLM concepts to exploring the features of this framework. Practical examples will guide you through essential steps for personalizing and launching your LlamaIndex projects. Additionally, you’ll overcome LLM limitations, build end-user applications, and acquire skills in ingesting, indexing, querying, and connecting dynamic knowledge bases, covering Generative AI and LLM, as well as LlamaIndex deployment. As you approach the conclusion, you’ll delve into customization, gaining a holistic grasp of LlamaIndex's capabilities and applications.By the end of the book, you’ll be able to resolve challenges in LLMs and build interactive AI-driven applications by applying best practices in prompt engineering and troubleshooting Generative AI projects.

Business Intelligence with Databricks SQL. Concepts, tools, and techniques for scaling business intelligence on the data lakehouse

Vihag Gupta

In this new era of data platform system design, data lakes and data warehouses are giving way to the lakehouse – a new type of data platform system that aims to unify all data analytics into a single platform. Databricks, with its Databricks SQL product suite, is the hottest lakehouse platform out there, harnessing the power of Apache Spark™, Delta Lake, and other innovations to enable data warehousing capabilities on the lakehouse with data lake economics.This book is a comprehensive hands-on guide that helps you explore all the advanced features, use cases, and technology components of Databricks SQL. You’ll start with the lakehouse architecture fundamentals and understand how Databricks SQL fits into it. The book then shows you how to use the platform, from exploring data, executing queries, building reports, and using dashboards through to learning the administrative aspects of the lakehouse – data security, governance, and management of the computational power of the lakehouse. You’ll also delve into the core technology enablers of Databricks SQL – Delta Lake and Photon. Finally, you’ll get hands-on with advanced SQL commands for ingesting data and maintaining the lakehouse.By the end of this book, you’ll have mastered Databricks SQL and be able to deploy and deliver fast, scalable business intelligence on the lakehouse.

Causal Inference and Discovery in Python. Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more

Aleksander Molak, Ajit Jaokar

Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely statistical mindset. Causal Inference and Discovery in Python helps you unlock the potential of causality.You’ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more. Each concept is accompanied by a theoretical explanation and a set of practical exercises with Python code.Next, you’ll dive into the world of causal effect estimation, consistently progressing towards modern machine learning methods. Step-by-step, you’ll discover Python causal ecosystem and harness the power of cutting-edge algorithms. You’ll further explore the mechanics of how “causes leave traces” and compare the main families of causal discovery algorithms.The final chapter gives you a broad outlook into the future of causal AI where we examine challenges and opportunities and provide you with a comprehensive list of resources to learn more.

ChatGPT for Accelerating Salesforce Development. Achieve faster, smarter, and more cost-effective Salesforce Delivery with ChatGPT

Andy Forbes, Philip Safir, Joseph Kubon, Francisco Fálder

ChatGPT for Salesforce Development is an indispensable guide for Salesforce business analysts, developers, testers, and product owners seeking to integrate ChatGPT into their workflow. This book delves into the intricacies of Salesforce design, configuration, coding, and testing, demonstrating how ChatGPT can simplify complex setups and enhance project team efficiency.With this book, you’ll unlock the effective use of ChatGPT for crafting user stories that align seamlessly with project goals, learn how to design and implement Salesforce flows, and quickly write clear, comprehensive, and high-quality project documentation. As you advance, you’ll leverage ChatGPT to write new Apex code, decipher existing code, and explore the development of web services and callouts. This book spans trigger creation and the development of Lightning Web Components (LWC), highlighting how these can accelerate the development process. Applying ChatGPT's debugging capabilities, you’ll swiftly identify and resolve Salesforce issues to uphold the integrity and performance of your Salesforce applications.By the end of this book, you’ll be adept at integrating ChatGPT at every stage of Salesforce project delivery, from initial configuration to final testing.

ChatGPT for Cybersecurity Cookbook. Learn practical generative AI recipes to supercharge your cybersecurity skills

Clint Bodungen, Aaron Crow

Are you ready to unleash the potential of AI-driven cybersecurity? This cookbook takes you on a journey toward enhancing your cybersecurity skills, whether you’re a novice or a seasoned professional. By leveraging cutting-edge generative AI and large language models such as ChatGPT, you'll gain a competitive advantage in the ever-evolving cybersecurity landscape.ChatGPT for Cybersecurity Cookbook shows you how to automate and optimize various cybersecurity tasks, including penetration testing, vulnerability assessments, risk assessment, and threat detection. Each recipe demonstrates step by step how to utilize ChatGPT and the OpenAI API to generate complex commands, write code, and even create complete tools. You’ll discover how AI-powered cybersecurity can revolutionize your approach to security, providing you with new strategies and techniques for tackling challenges. As you progress, you’ll dive into detailed recipes covering attack vector automation, vulnerability scanning, GPT-assisted code analysis, and more. By learning to harness the power of generative AI, you'll not only expand your skillset but also increase your efficiency.By the end of this cybersecurity book, you’ll have the confidence and knowledge you need to stay ahead of the curve, mastering the latest generative AI tools and techniques in cybersecurity.

ChatGPT Prompts Book - Precision Prompts, Priming, Training & AI Writing Techniques for Mortals. Crafting Precision Prompts and Exploring AI Writing with ChatGPT

Oliver Theobald

The course embarks on an enlightening journey through the world of ChatGPT, starting from the very basics of understanding what ChatGPT is, to delving deep into the mechanics of crafting precision prompts that unlock its full potential. From the outset, you'll be introduced to the foundational elements that make ChatGPT an indispensable tool for a wide range of applications, setting the stage for a comprehensive exploration of its capabilities.As we progress, the course meticulously unfolds the layers of prompt writing techniques, priming strategies, and training methodologies that are designed to enhance your interaction with AI. You'll learn how to craft prompts for common use cases, navigate the nuances of content creation, translation tasks, and personalized tutoring, all while leveraging ChatGPT's advanced AI art capabilities.The course culminates by focusing on practical applications and exploring advanced prompt training and role prompting techniques. This final stretch is designed to solidify your understanding and empower you with the confidence to employ ChatGPT across various scenarios, from professional content writing to creative explorations.

Comet for Data Science. Enhance your ability to manage and optimize the life cycle of your data science project

Angelica Lo Duca, Gideon Mendels

This book provides concepts and practical use cases which can be used to quickly build, monitor, and optimize data science projects. Using Comet, you will learn how to manage almost every step of the data science process from data collection through to creating, deploying, and monitoring a machine learning model.The book starts by explaining the features of Comet, along with exploratory data analysis and model evaluation in Comet. You’ll see how Comet gives you the freedom to choose from a selection of programming languages, depending on which is best suited to your needs. Next, you will focus on workspaces, projects, experiments, and models. You will also learn how to build a narrative from your data, using the features provided by Comet. Later, you will review the basic concepts behind DevOps and how to extend the GitLab DevOps platform with Comet, further enhancing your ability to deploy your data science projects. Finally, you will cover various use cases of Comet in machine learning, NLP, deep learning, and time series analysis, gaining hands-on experience with some of the most interesting and valuable data science techniques available.By the end of this book, you will be able to confidently build data science pipelines according to bespoke specifications and manage them through Comet.

Creators of Intelligence. Industry secrets from AI leaders that you can easily apply to advance your data science career

Dr. Alex Antic, John K. Thompson

A Gartner prediction in 2018 led to numerous articles stating that 85% of AI and machine learning projects fail to deliver.” Although it's unclear whether a mass extinction event occurred for AI implementations at the end of 2022, the question remains: how can I ensure that my project delivers value and doesn't become a statistic?The demand for data scientists has only grown since 2015, when they were dubbed the new “rock stars” of business. But how can you become a data science rock star? As a new senior data leader, how can you build and manage a productive team? And what is the path to becoming a chief data officer?Creators of Intelligence is a collection of in-depth, one-on-one interviews where Dr. Alex Antic, a recognized data science leader, explores the answers to these questions and more with some of the world's leading data science leaders and CDOs.Interviews with: Cortnie Abercrombie, Edward Santow, Kshira Saagar, Charles Martin, Petar Veličković, Kathleen Maley, Kirk Borne, Nikolaj Van Omme, Jason Tamara Widjaja, Jon Whittle, Althea Davis, Igor Halperin, Christina Stathopoulos, Angshuman Ghosh, Maria Milosavljevic, Dr. Meri Rosich, Dat Tran, and Stephane Doyen.