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Mastering AI (Artificial Intelligence)

Mastering AI (Artificial Intelligence) PDF Author: Kris Hermans
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 213

Book Description
In a world where artificial intelligence is rapidly reshaping every aspect of our lives, "Mastering AI" serves as your definitive guide to understanding and harnessing this transformative technology. This comprehensive manual cuts through the hype, demystifying AI's complexities, and making it accessible to readers across the spectrum of expertise. Author Kris Hermans, a recognized authority in AI for Cybersecurity, expertly navigates the vast landscape of artificial intelligence, blending theoretical foundations with practical applications. Whether you're a beginner eager to grasp the basics or a seasoned professional looking to refine your skills, "Mastering AI" is your roadmap to successfully navigating the fascinating world of AI.

Mastering AI (Artificial Intelligence)

Mastering AI (Artificial Intelligence) PDF Author: Kris Hermans
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 213

Book Description
In a world where artificial intelligence is rapidly reshaping every aspect of our lives, "Mastering AI" serves as your definitive guide to understanding and harnessing this transformative technology. This comprehensive manual cuts through the hype, demystifying AI's complexities, and making it accessible to readers across the spectrum of expertise. Author Kris Hermans, a recognized authority in AI for Cybersecurity, expertly navigates the vast landscape of artificial intelligence, blending theoretical foundations with practical applications. Whether you're a beginner eager to grasp the basics or a seasoned professional looking to refine your skills, "Mastering AI" is your roadmap to successfully navigating the fascinating world of AI.

Mastering Machine Learning Algorithms

Mastering Machine Learning Algorithms PDF Author: Giuseppe Bonaccorso
Publisher: Packt Publishing Ltd
ISBN: 1788625900
Category : Computers
Languages : en
Pages : 567

Book Description
Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and more Book Description Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learn Explore how a ML model can be trained, optimized, and evaluated Understand how to create and learn static and dynamic probabilistic models Successfully cluster high-dimensional data and evaluate model accuracy Discover how artificial neural networks work and how to train, optimize, and validate them Work with Autoencoders and Generative Adversarial Networks Apply label spreading and propagation to large datasets Explore the most important Reinforcement Learning techniques Who this book is for This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.

Mastering AI Tools and Techniques

Mastering AI Tools and Techniques PDF Author: Ernest R. Tello
Publisher: Sams Technical Publishing
ISBN:
Category : Computers
Languages : en
Pages : 574

Book Description
This book is focuses on AI=Artificial Inteligence as well as its impact on such practical areas as advanced user interfaces, intelligent data management , and knowledge acquisition.In this pages you will learn:* What AI is and how to put AI to work for you, *Which AI tools currently exist, how they work, and what you can do with them, *The fundamentals of natural langugage and decision modeling systems, *How to develop an expert system, *Advanced AI concepts, including truth maintenance, planing systems, understanding, and machine learning, *AI programming and AI programming languages, including LISP, Prolog, and Smaltalk.

Mastering Machine Learning for Penetration Testing

Mastering Machine Learning for Penetration Testing PDF Author: Chiheb Chebbi
Publisher: Packt Publishing Ltd
ISBN: 178899311X
Category : Language Arts & Disciplines
Languages : en
Pages : 264

Book Description
Become a master at penetration testing using machine learning with Python Key Features Identify ambiguities and breach intelligent security systems Perform unique cyber attacks to breach robust systems Learn to leverage machine learning algorithms Book Description Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it’s important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you’ve gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you’ll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you’ll focus on topics such as network intrusion detection and AV and IDS evasion. We’ll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system. By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system. What you will learn Take an in-depth look at machine learning Get to know natural language processing (NLP) Understand malware feature engineering Build generative adversarial networks using Python libraries Work on threat hunting with machine learning and the ELK stack Explore the best practices for machine learning Who this book is for This book is for pen testers and security professionals who are interested in learning techniques to break an intelligent security system. Basic knowledge of Python is needed, but no prior knowledge of machine learning is necessary.

Mastering .NET Machine Learning

Mastering .NET Machine Learning PDF Author: Jamie Dixon
Publisher: Packt Publishing Ltd
ISBN: 1785881191
Category : Computers
Languages : en
Pages : 358

Book Description
Master the art of machine learning with .NET and gain insight into real-world applications About This Book Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0 Set up your business application to start using machine learning techniques Familiarize the user with some of the more common .NET libraries for machine learning Implement several common machine learning techniques Evaluate, optimize and adjust machine learning models Who This Book Is For This book is targeted at .Net developers who want to build complex machine learning systems. Some basic understanding of data science is required. What You Will Learn Write your own machine learning applications and experiments using the latest .NET framework, including .NET Core 1.0 Set up your business application to start using machine learning. Accurately predict the future using regressions. Discover hidden patterns using decision trees. Acquire, prepare, and combine datasets to drive insights. Optimize business throughput using Bayes Classifier. Discover (more) hidden patterns using KNN and Naive Bayes. Discover (even more) hidden patterns using K-Means and PCA. Use Neural Networks to improve business decision making while using the latest ASP.NET technologies. Explore “Big Data”, distributed computing, and how to deploy machine learning models to IoT devices – making machines self-learning and adapting Along the way, learn about Open Data, Bing maps, and MBrace In Detail .Net is one of the widely used platforms for developing applications. With the meteoric rise of Machine learning, developers are now keen on finding out how can they make their .Net applications smarter. Also, .NET developers are interested into moving into the world of devices and how to apply machine learning techniques to, well, machines. This book is packed with real-world examples to easily use machine learning techniques in your business applications. You will begin with introduction to F# and prepare yourselves for machine learning using .NET framework. You will be writing a simple linear regression model using an example which predicts sales of a product. Forming a base with the regression model, you will start using machine learning libraries available in .NET framework such as Math.NET, Numl.NET and Accord.NET with the help of a sample application. You will then move on to writing multiple linear regressions and logistic regressions. You will learn what is open data and the awesomeness of type providers. Next, you are going to address some of the issues that we have been glossing over so far and take a deep dive into obtaining, cleaning, and organizing our data. You will compare the utility of building a KNN and Naive Bayes model to achieve best possible results. Implementation of Kmeans and PCA using Accord.NET and Numl.NET libraries is covered with the help of an example application. We will then look at many of issues confronting creating real-world machine learning models like overfitting and how to combat them using confusion matrixes, scaling, normalization, and feature selection. You will now enter into the world of Neural Networks and move your line of business application to a hybrid scientific application. After you have covered all the above machine learning models, you will see how to deal with very large datasets using MBrace and how to deploy machine learning models to Internet of Thing (IoT) devices so that the machine can learn and adapt on the fly Style and approach This book will guide you in learning everything about how to tackle the flood of data being encountered these days in your .NET applications with the help of popular machine learning libraries offered by the .NET framework.

The AI Book

The AI Book PDF Author: Ivana Bartoletti
Publisher: John Wiley & Sons
ISBN: 1119551927
Category : Business & Economics
Languages : en
Pages : 782

Book Description
Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important

Mastering Machine Learning

Mastering Machine Learning PDF Author: Cybellium Ltd
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 335

Book Description
Are you ready to become a master of machine learning? In "Mastering Machine Learning" by Kris Hermans, you'll embark on a transformative journey that will empower you with the skills and knowledge needed to conquer the world of data-driven intelligence. Discover Cutting-Edge Techniques and Practical Applications From self-driving cars to personalized recommendations, machine learning is transforming industries and reshaping the way we live and work. In this comprehensive guide, Kris Hermans equips you with the tools to harness the power of machine learning. Dive into the core concepts, algorithms, and models that underpin this revolutionary field. Become a Proficient Practitioner Whether you're a beginner or an experienced professional, this book provides a clear and structured path to mastering machine learning. Through hands-on examples and real-world case studies, you'll gain practical expertise in implementing machine learning models and solving complex problems. Kris Hermans guides you through the process, ensuring you develop a deep understanding of the techniques and algorithms that drive intelligent systems. From Fundamentals to Advanced Topics "Mastering Machine Learning" covers the full spectrum of machine learning, starting with the foundations of supervised and unsupervised learning and progressing to reinforcement learning, neural networks, and deep learning. Explore diverse models and learn how to choose the right approach for different applications. With this knowledge, you'll be able to tackle real-world challenges with confidence. Unlock the Potential of Machine Learning Across Industries Discover how machine learning is revolutionizing industries such as finance, healthcare, e-commerce, and cybersecurity. Through captivating case studies, you'll witness the transformative impact of machine learning and gain insights into how organizations are leveraging this technology to drive innovation, improve decision-making, and achieve unprecedented success. Navigate Ethical Considerations As machine learning becomes increasingly powerful, it's crucial to consider the ethical implications. "Mastering Machine Learning" addresses these important considerations head-on. Learn about the ethical challenges and responsibilities associated with machine learning applications and gain the knowledge to make informed, ethical decisions in your own work.

Mastering Artificial Intelligence and Machine Learning

Mastering Artificial Intelligence and Machine Learning PDF Author: Dr. L. Sridhara Rao
Publisher: LAP Lambert Academic Publishing
ISBN: 6205519852
Category : Computers
Languages : en
Pages : 198

Book Description
The book “Mastering Artificial Intelligence and Machine Learning” provides the in-depth knowledge in the field of Artificial Learning, Expert Systems, Natural Language Processing, Deep Learning, Machine Learning etc., to the graduate, post graduate and research scholars. When we talk about Artificial Intelligence, it often evokes a world of robots or futuristic technologies. However, Artificial Intelligence is already part of our daily lives. It is impacting the business world more. Knowledge Engineering is an essential part of AI research. Machines and programs need to have bountiful information related to the world to often act and react like human beings. Machine learning is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.

AI Fundamentals

AI Fundamentals PDF Author: John A Robinson
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0

Book Description
Embark on a captivating exploration of what AI truly means and its underlying principles. Understand the differences between Narrow AI and General AI and how they are revolutionizing industries. "AI Fundamentals-Mastering the Basics of Artificial Intelligence" is your essential companion to understanding AI without drowning in technical jargon. Whether you're a curious individual, a business professional, or simply someone intrigued by the future, this book will empower you to embrace the limitless possibilities of Artificial Intelligence. Unlock the secrets of AI and embark on a captivating journey to the cutting-edge world of tomorrow. Let "AI Fundamentals-Mastering the Basics of Artificial Intelligence" be your beacon to navigate through the AI revolution in the most comprehensible and enlightening way. Grab your copy now and witness the magic of AI come alive!

AI Unleashed: A Holistic Guide to Mastering Artificial Intelligence

AI Unleashed: A Holistic Guide to Mastering Artificial Intelligence PDF Author: Tanjimul Islam Tareq
Publisher: BookRix
ISBN: 3755451344
Category : Juvenile Nonfiction
Languages : en
Pages : 28

Book Description
Embark on a transformative journey through the realm of artificial intelligence with "AI Unleashed: A Holistic Guide to Mastering Artificial Intelligence." In this comprehensive and unique guide, you'll uncover the depths of AI's complexities, from foundational concepts to cutting-edge techniques that are shaping the future. From the evolution of AI's journey from fiction to reality, to the powerful insights of unsupervised learning, deep learning, and reinforcement learning, this book equips you with the knowledge to unravel AI's intricacies. Through vivid explanations, real-world examples, and immersive chapters, you'll traverse the landscape of supervised and unsupervised learning, delve into neural networks and advanced algorithms, and comprehend the ethical considerations that underpin responsible AI development. But "AI Unleashed" doesn't stop at theory—it propels you into action. You'll discover the practical aspects of data preprocessing, model tuning, and deployment strategies that are pivotal for creating AI solutions that work seamlessly in the real world. Moreover, you'll explore the intersections of AI with diverse industries, from healthcare and finance to quantum computing, positioning you at the forefront of innovation. As you journey through these pages, you'll not only gain a deep understanding of AI's intricacies but also develop the skills to build intelligent systems that create positive impacts. Whether you're a seasoned AI practitioner or a curious beginner, "AI Unleashed" empowers you to unlock the boundless potential of artificial intelligence and embark on a path of continuous learning that propels you forward in the dynamic world of AI innovation.