Cybernetics Intelligence With Python PDF Download
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Author: Prof. Frank Appiah
Publisher: Lulu.com
ISBN: 0359686397
Category :
Languages : en
Pages : 414
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Book Description
Author: Prof. Frank Appiah
Publisher: Lulu.com
ISBN: 0359686397
Category :
Languages : en
Pages : 414
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Book Description
Author: Howard E. Poston, III
Publisher: John Wiley & Sons
ISBN: 1119850657
Category : Computers
Languages : en
Pages : 240
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Book Description
Discover an up-to-date and authoritative exploration of Python cybersecurity strategies Python For Cybersecurity: Using Python for Cyber Offense and Defense delivers an intuitive and hands-on explanation of using Python for cybersecurity. It relies on the MITRE ATT&CK framework to structure its exploration of cyberattack techniques, attack defenses, and the key cybersecurity challenges facing network administrators and other stakeholders today. Offering downloadable sample code, the book is written to help you discover how to use Python in a wide variety of cybersecurity situations, including: Reconnaissance, resource development, initial access, and execution Persistence, privilege escalation, defense evasion, and credential access Discovery, lateral movement, collection, and command and control Exfiltration and impact Each chapter includes discussions of several techniques and sub-techniques that could be used to achieve an attacker's objectives in any of these use cases. The ideal resource for anyone with a professional or personal interest in cybersecurity, Python For Cybersecurity offers in-depth information about a wide variety of attacks and effective, Python-based defenses against them.
Author: Dr. Frank Appiah
Publisher: Lulu.com
ISBN: 0359643604
Category :
Languages : en
Pages : 144
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Book Description
Author: William Dimick
Publisher:
ISBN: 9781914412240
Category :
Languages : en
Pages : 144
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Book Description
Do you want to find out how to use Python code to manage and improve Artificial intelligence and Deep learning? Are you looking for an easy training guide for programmers and data scientists? If yes, then keep reading... Artificial intelligence is a branch of computer science that seeks to develop computer systems that are capable of human-like intelligence. You can have artificial intelligence that replicates the human mind implemented this way rather than just having a computer system that mimics and the entire human brain. The latter is probably something very far off, if it is ever achieved. Artificially intelligent systems run independently. Computer systems based on artificial intelligence need to be trained, but once trained, they can operate on their own without human intervention. In the case of human intelligence, the more data you are exposed to, the better you get at solving problems related to that data. Similarly, computer systems based on artificial intelligence self-adjust to make themselves perform better. This is quite a contrast with conventional computer systems, which only do what you tell them to do, and without humans rewriting the programs that run them, they don't get any better at what they do. This is a crucial point to focus on, because the kinds of systems that we are going to talk about in this book will adjust themselves and get better, without any human intervention whatsoever. Once they are deployed, the human operators might not even understand why the artificially intelligent computer system makes the decisions it does, or how it is making those decisions. This book covers: - Machine Learning - Concepts and Terms - Data Scrubbing - Data Mining Categories - Difference between Machine Learning and AI So, ready to get started? Order Now!
Author: Soma Halder
Publisher: Packt Publishing Ltd
ISBN: 178899096X
Category : Computers
Languages : en
Pages : 306
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Book Description
Get into the world of smart data security using machine learning algorithms and Python libraries Key FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learnUse machine learning algorithms with complex datasets to implement cybersecurity conceptsImplement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problemsLearn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDAUnderstand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimesUse TensorFlow in the cybersecurity domain and implement real-world examplesLearn how machine learning and Python can be used in complex cyber issuesWho this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book
Author: Jason Bourny
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
Python for OSINT: Tracking and Profiling Targets Unleash the Power of Python for Open Source Intelligence! Are you ready to elevate your cyber intelligence skills? "Python for OSINT: Tracking and Profiling Targets" is your essential guide to mastering the art of open-source intelligence (OSINT) using the Python programming language. Designed for hackers, pentesters, and cybersecurity professionals, this book equips you with the tools and techniques to uncover and analyze valuable information from publicly available sources. Key Features and Benefits: Advanced Web Scraping Dive deep into sophisticated web scraping methods. Learn how to extract valuable data from websites efficiently, bypassing common obstacles such as CAPTCHAs and anti-scraping mechanisms. This book provides you with the knowledge to collect and process vast amounts of data quickly using Python, Bash scripting, and PowerShell. Comprehensive Data Extraction Master the art of data extraction from various online sources, including social media platforms, forums, and databases. Understand how to use Python libraries and tools to gather intelligence and profile targets effectively. Techniques for network security, steganography, and cryptography are also covered. Real-World OSINT Projects Engage with practical, hands-on projects that simulate real-world scenarios. Each chapter includes exercises and examples that take you from theory to practice, ensuring you gain actionable skills. Projects include Python automation, hacking tools, and data extraction from IoT devices. Python Programming for Intelligence Gathering Whether you're a beginner or an experienced programmer, this book offers a thorough introduction to Python, focusing on its application in OSINT. Learn to write powerful scripts that automate the process of tracking and profiling targets. Explore advanced Python projects, Python machine learning, and how to run a Python script effectively. Ethical Hacking and Compliance Understand the ethical considerations and legal boundaries of OSINT. This book emphasizes responsible usage of intelligence-gathering techniques, ensuring you stay within legal and ethical limits while conducting investigations. Insights into black hat hacking, gray hat Python, and ethical hacking books are included. Cutting-Edge Techniques Stay ahead of the game with the latest OSINT methodologies and tools. This book is continuously updated to include new strategies and technologies, ensuring you're always equipped with the most current knowledge. Topics like black web, Bluetooth device hacking, and micropython are covered. Why Choose This Book? "Python for OSINT" is not just another technical manual; it's your pathway to becoming a proficient intelligence analyst. Written by industry experts, this book simplifies complex concepts into clear, actionable steps, making it accessible for both novices and seasoned professionals. Who Should Read This Book? Aspiring Hackers: Start with a solid foundation in OSINT techniques and tools. Pentesters: Enhance your skill set with advanced intelligence-gathering strategies. Cybersecurity Professionals: Stay updated with the latest OSINT techniques to protect your organization effectively. Python Enthusiasts: Leverage your programming skills to gather and analyze intelligence like a pro. Propel Your Cyber Intelligence Career Forward Invest in your future by mastering the art of OSINT with Python. "Python for OSINT: Tracking and Profiling Targets" is your indispensable resource for becoming a leader in the field of cyber intelligence. Don't miss out on this essential guide. Add it to your cart now and take the first step towards becoming an OSINT expert!
Author: Russel R Russo
Publisher:
ISBN: 9781801118590
Category :
Languages : en
Pages : 0
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Book Description
Are you fascinated by Machine Learning but it seems too complicated?Do you have some coding skills but you want to go deeper in Python and Machine Learning? If this is you, please keep reading: you are in the right place, looking at the right book. Since you are reading this you are probably aware of how important Artificial Intelligence is in these days. In your everyday life Artificial Intelligence is all around you. Every time you buy a product on Amazon, follow a new profile on Instagram, listen to a song on Spotify or reserve a room on Booking, they are learning something out of your behavior. And these are just the most visible aspects of how Machine Learning is having an impact on our lives. Everyone knows (well, almost everyone) how important Machine Learning is for the growth and success of the biggest tech companies, and many people know about the Machine Learning impact in science, medicine and statistics. Also, it is quite commonly known that Artificial Intelligence, Machine Learning, and the mastering of their most important language, Python, can offer a lot of possibilities in work and business. And you yourself are probably thinking "I surely can see that opportunity, but how can I seize it?" Well, if you kept reading so far you are on the right track to answer your question. In Machine Learning with Python you will find: Why python is the best language for Machine Learning How to bring your ideas into a computer The smartest way to approach Machine Learning How to deal with variables and data Tips and tricks for a smooth and painless journey into artificial intelligence The most common myths about Machine Learning debunked So, whether you decided to start now or to go deeper into Artificial Intelligence, Machine Learning and Python Programming, you will only have two unanswered questions right now: "what is the best way to do it? And when is the best time to start?" An easy, clear and complete guide as Machine Learning with Python is the answer to your first question, and about the second one, well, that's an easy one: the best time is NOW! Buy Machine Learning with Python now and start mastering the secrets of Artificial Intelligence.
Author: Patrick J
Publisher: GitforGits
ISBN: 8119177630
Category : Computers
Languages : en
Pages : 260
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Book Description
This book aspires young graduates and programmers to become AI engineers and enter the world of artificial intelligence by combining powerful Python programming with artificial intelligence. Beginning with the fundamentals of Python programming, the book gradually progresses to machine learning, where readers learn to implement Python in developing predictive models. The book provides a clear and accessible explanation of machine learning, incorporating practical examples and exercises that strengthen understanding. We go deep into deep learning, another vital component of AI. Readers gain a thorough understanding of how Python's frameworks and libraries can be used to create sophisticated neural networks and algorithms, which are required for tasks such as image and speech recognition. Natural Language Processing is also covered in the book, with fundamental concepts and techniques for interpreting and generating human-like language covered. The book's focus on computer vision and reinforcement learning is distinctive, presenting these cutting-edge AI fields in an approachable manner. Readers will learn how to use Python's intuitive programming paradigm to create systems that interpret visual data and make intelligent decisions based on environmental interactions. The book focuses on ethical AI development and responsible programming, emphasizing the importance of developing AI that is fair, transparent, and accountable. Each chapter is designed to improve learning by including practical examples, case studies, and exercises that provide hands-on experience. This book is an excellent starting point for anyone interested in becoming an AI engineer, providing the necessary foundational knowledge and skills to delve into the fascinating world of artificial intelligence. Key Learnings Explore Python basics and AI integration for real-world application and career advancement. Experience the power of Python in AI with practical machine learning techniques. Practice Python's deep learning tools for innovative AI solution development. Dive into NLP with Python to revolutionize data interpretation and communication strategies. Simple yet practical understanding of reinforcement learning for strategic AI decision making. Uncover ethical AI development and frameworks, and concepts of responsible and trustworthy AI. Harness Python's capabilities for creating AI applications with a focus on fairness and bias. Table of Content Introduction to Artificial Intelligence Python for AI Data as Fuel for AI Machine Learning Foundation Essentials of Deep Learning NLP and Computer Vision Hands-on Reinforcement Learning Ethics to AI
Author: Chong Li
Publisher: CRC Press
ISBN: 1351006606
Category : Computers
Languages : en
Pages : 249
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Book Description
Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields of reinforcement learning (RL) and cyber-physical systems (CPSs). Rooted in behavioral psychology, RL is one of the primary strands of machine learning. Different from other machine learning algorithms, such as supervised learning and unsupervised learning, the key feature of RL is its unique learning paradigm, i.e., trial-and-error. Combined with the deep neural networks, deep RL become so powerful that many complicated systems can be automatically managed by AI agents at a superhuman level. On the other hand, CPSs are envisioned to revolutionize our society in the near future. Such examples include the emerging smart buildings, intelligent transportation, and electric grids. However, the conventional hand-programming controller in CPSs could neither handle the increasing complexity of the system, nor automatically adapt itself to new situations that it has never encountered before. The problem of how to apply the existing deep RL algorithms, or develop new RL algorithms to enable the real-time adaptive CPSs, remains open. This book aims to establish a linkage between the two domains by systematically introducing RL foundations and algorithms, each supported by one or a few state-of-the-art CPS examples to help readers understand the intuition and usefulness of RL techniques. Features Introduces reinforcement learning, including advanced topics in RL Applies reinforcement learning to cyber-physical systems and cybersecurity Contains state-of-the-art examples and exercises in each chapter Provides two cybersecurity case studies Reinforcement Learning for Cyber-Physical Systems with Cybersecurity Case Studies is an ideal text for graduate students or junior/senior undergraduates in the fields of science, engineering, computer science, or applied mathematics. It would also prove useful to researchers and engineers interested in cybersecurity, RL, and CPS. The only background knowledge required to appreciate the book is a basic knowledge of calculus and probability theory.
Author: Stephen Lynch
Publisher: CRC Press
ISBN: 100088967X
Category : Computers
Languages : en
Pages : 334
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Book Description
Python for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web. Support Material GitHub Repository of Python Files and Notebooks: https://github.com/proflynch/CRC-Press/ Solutions to All Exercises: Section 1: An Introduction to Python: https://drstephenlynch.github.io/webpages/Solutions_Section_1.html Section 2: Python for Scientific Computing: https://drstephenlynch.github.io/webpages/Solutions_Section_2.html Section 3: Artificial Intelligence: https://drstephenlynch.github.io/webpages/Solutions_Section_3.html
