THE FUTURE OF CLOUD: INTEGRATING AI, ML, AND GENERATIVE AI FOR SCALABLE SOLUTIONS PDF Download
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Author: Chandrakanth Rao Madhavaram
Publisher: JEC PUBLICATION
ISBN: 9361754424
Category : Computers
Languages : en
Pages : 216
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Book Description
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Author: Chandrakanth Rao Madhavaram
Publisher: JEC PUBLICATION
ISBN: 9361754424
Category : Computers
Languages : en
Pages : 216
Get Book Here
Book Description
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Author: Arun Kumar Ramachandran Sumangala Devi
Publisher: JEC PUBLICATION
ISBN: 9361753290
Category : Computers
Languages : en
Pages : 171
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Book Description
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Author: Prabhu TL
Publisher: NestFame Creations Pvt Ltd.
ISBN:
Category : Computers
Languages : en
Pages : 224
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Book Description
In the era of groundbreaking technological advancements, the book "100 Best Generative AI Tools" is your passport to an exhilarating expedition through the realms of creativity, imagination, and innovation. This captivating guide unveils a curated selection of the most remarkable and transformative generative AI tools that are reshaping the landscape of human ingenuity across a multitude of industries. Unlocking the Power of Generative AI: Imagine a world where machines possess the remarkable ability to generate art, music, literature, and even entire virtual realities. In "100 Best Generative AI Tools," you'll venture into this awe-inspiring realm, where algorithms fuse with creativity to produce captivating and unprecedented results. Whether you're an artist, a musician, a writer, or an innovator, this book empowers you to harness the potential of generative AI to amplify your creative endeavors. A Treasury of Creative Possibilities: This book serves as a treasure trove of innovative generative AI tools, meticulously curated to offer a diverse and comprehensive range of applications. From producing mesmerizing visual masterpieces to composing evocative musical compositions, and from crafting compelling narratives to designing immersive virtual landscapes—each tool is a gateway to limitless creative possibilities. Behind the Algorithmic Curtain: Delve deeper into the intricate workings of these generative AI tools as you unravel the science behind the algorithms. "100 Best Generative AI Tools" deciphers complex concepts into accessible insights, making it a captivating read for both enthusiasts and those new to the field. Explore how neural networks, deep learning, and cutting-edge technology collaborate harmoniously to produce works of art that rival human creativity. Crossing Boundaries and Industries: The impact of generative AI knows no bounds, transcending industries and reshaping the way we perceive creativity. Whether you're a fashion designer pushing the boundaries of design, a game developer crafting immersive digital experiences, or a scientist generating data-driven insights, the tools showcased in this book will spark your imagination and transform your approach to innovation. Empowering Creative Minds: "100 Best Generative AI Tools" goes beyond mere description; it provides you with the tools and knowledge to unleash your creative potential. Whether you're a curious novice or an experienced artist, this book equips you with the resources to embark on a journey of experimentation, discovery, and artistic evolution. Shape the Future of Creativity: As you delve into the pages of "100 Best Generative AI Tools," you become part of a transformative movement that is redefining the boundaries of human creativity. With these tools at your fingertips, you have the power to amplify your artistic voice, challenge traditional norms, and craft a future where the fusion of AI and imagination knows no limits. Join the Creative Revolution: Are you ready to join the ranks of visionaries who are seamlessly blending art, technology, and innovation? "100 Best Generative AI Tools" is your guide to embracing the future, where the canvas of creativity knows no boundaries and the brush strokes of imagination are powered by algorithms. Step into a world where your creative potential knows no limits, and let the journey of innovation begin.
Author: Gomathi Sankar, Jeganathan
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 468
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Book Description
As generative AI rapidly advances with the field of artificial intelligence, its presence poses significant ethical, security, and data management challenges. While this technology encourages innovation across various industries, ethical concerns regarding the potential misuse of AI-generated content for misinformation or manipulation may arise. The risks of AI-generated deepfakes and cyberattacks demand more research into effective security tactics. The supervision of datasets required to train generative AI models raises questions about privacy, consent, and responsible data management. As generative AI evolves, further research into the complex issues regarding its potential is required to safeguard ethical values and security of people’s data. Generative AI and Implications for Ethics, Security, and Data Management explores the implications of generative AI across various industries who may use the tool for improved organizational development. The security and data management benefits of generative AI are outlined, while examining the topic within the lens of ethical and social impacts. This book covers topics such as cybersecurity, digital technology, and cloud storage, and is a useful resource for computer engineers, IT professionals, technicians, sociologists, healthcare workers, researchers, scientists, and academicians.
Author: Introbooks
Publisher:
ISBN:
Category :
Languages : en
Pages : 50
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Book Description
In these highly competitive times and with so many technological advancements, it is impossible for any industry to remain isolated and untouched by innovations. In this era of digital economy, the banking sector cannot exist and operate without the various digital tools offered by the ever new innovations happening in the field of Artificial Intelligence (AI) and its sub-set technologies. New technologies have enabled incredible progression in the finance industry. Artificial Intelligence (AI) and Machine Learning (ML) have provided the investors and customers with more innovative tools, new types of financial products and a new potential for growth.According to Cathy Bessant (the Chief Operations and Technology Officer, Bank of America), AI is not just a technology discussion. It is also a discussion about data and how it is used and protected. She says, "In a world focused on using AI in new ways, we're focused on using it wisely and responsibly."
Author: Chris Fregly
Publisher: "O'Reilly Media, Inc."
ISBN: 1492079367
Category : Computers
Languages : en
Pages : 524
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Book Description
With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more
Author: David Ping
Publisher: Packt Publishing Ltd
ISBN: 180512482X
Category : Computers
Languages : en
Pages : 603
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Book Description
Design, build, and secure scalable machine learning (ML) systems to solve real-world business problems with Python and AWS Purchase of the print or Kindle book includes a free PDF eBook Key Features Go in-depth into the ML lifecycle, from ideation and data management to deployment and scaling Apply risk management techniques in the ML lifecycle and design architectural patterns for various ML platforms and solutions Understand the generative AI lifecycle, its core technologies, and implementation risks Book DescriptionDavid Ping, Head of GenAI and ML Solution Architecture for global industries at AWS, provides expert insights and practical examples to help you become a proficient ML solutions architect, linking technical architecture to business-related skills. You'll learn about ML algorithms, cloud infrastructure, system design, MLOps , and how to apply ML to solve real-world business problems. David explains the generative AI project lifecycle and examines Retrieval Augmented Generation (RAG), an effective architecture pattern for generative AI applications. You’ll also learn about open-source technologies, such as Kubernetes/Kubeflow, for building a data science environment and ML pipelines before building an enterprise ML architecture using AWS. As well as ML risk management and the different stages of AI/ML adoption, the biggest new addition to the handbook is the deep exploration of generative AI. By the end of this book , you’ll have gained a comprehensive understanding of AI/ML across all key aspects, including business use cases, data science, real-world solution architecture, risk management, and governance. You’ll possess the skills to design and construct ML solutions that effectively cater to common use cases and follow established ML architecture patterns, enabling you to excel as a true professional in the field.What you will learn Apply ML methodologies to solve business problems across industries Design a practical enterprise ML platform architecture Gain an understanding of AI risk management frameworks and techniques Build an end-to-end data management architecture using AWS Train large-scale ML models and optimize model inference latency Create a business application using artificial intelligence services and custom models Dive into generative AI with use cases, architecture patterns, and RAG Who this book is for This book is for solutions architects working on ML projects, ML engineers transitioning to ML solution architect roles, and MLOps engineers. Additionally, data scientists and analysts who want to enhance their practical knowledge of ML systems engineering, as well as AI/ML product managers and risk officers who want to gain an understanding of ML solutions and AI risk management, will also find this book useful. A basic knowledge of Python, AWS, linear algebra, probability, and cloud infrastructure is required before you get started with this handbook.
Author: Dr. Asma Asfour
Publisher: Asma Asfour
ISBN:
Category : Computers
Languages : en
Pages : 195
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Book Description
This book, "AI-Powered Productivity," aims to provide a guide to understanding, utilizing AI and generative tools in various professional settings. The primary purpose of this book is to offer readers a deep dive into the concepts, tools, and practices that define the current AI landscape. From foundational principles to advanced applications, this book is structured to cater to both beginners and professionals looking to enhance their knowledge and skills in AI. This book is divided into nine chapters, each focusing on a specific aspect of AI and its practical applications: Chapter 1 introduces the basic concepts of AI, its impact on various sectors, and key factors driving its rapid advancement, along with an overview of generative AI tools. Chapter 2 delves into large language models like ChatGPT, Google Gemini, Claude, Microsoft's Turing NLG, and Facebook's BlenderBot, exploring their integration with multimodal technologies and their effects on professional productivity. Chapter 3 offers a practical guide to mastering LLM prompting and customization, including tutorials on crafting effective prompts and advanced techniques, as well as real-world examples of AI applications. Chapter 4 examines how AI can enhance individual productivity, focusing on professional and personal benefits, ethical use, and future trends. Chapter 5 addresses data-driven decision- making, covering data analysis techniques, AI in trend identification, consumer behavior analysis, strategic planning, and product development. Chapter 6 discusses strategic and ethical considerations of AI, including AI feasibility, tool selection, multimodal workflows, and best practices for ethical AI development and deployment. Chapter 7 highlights the role of AI in transforming training and professional development, covering structured training programs, continuous learning initiatives, and fostering a culture of innovation and experimentation. Chapter 8 provides a guide to successfully implementing AI in organizations, discussing team composition, collaborative approaches, iterative development processes, and strategic alignment for AI initiatives. Finally, Chapter 9 looks ahead to the future of work, preparing readers for the AI revolution by addressing training and education, career paths, common fears, and future trends in the workforce. The primary audience for the book is professionals seeking to enhance productivity and organizations or businesses. For professionals, the book targets individuals from various industries, reflecting its aim to reach a broad audience across different professional fields. It is designed for employees at all levels, offering valuable insights to both newcomers to AI and seasoned professionals. Covering a range of topics from foundational concepts to advanced applications, the book is particularly relevant for those interested in improving efficiency, with a strong emphasis on practical applications and productivity tools to optimize work processes. For organizations and businesses, the book serves as a valuable resource for decision-makers and managers, especially with chapters on data-driven decision-making, strategic considerations, and AI implementation. HR and training professionals will find the focus on AI in training and development beneficial for talent management, while IT and technology teams will appreciate the information on AI tools and concepts.
Author: Clarence Chio
Publisher: "O'Reilly Media, Inc."
ISBN: 1491979852
Category : Computers
Languages : en
Pages : 394
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Book Description
Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions
Author: Bernard Marr
Publisher: John Wiley & Sons
ISBN: 1119548985
Category : Business & Economics
Languages : en
Pages : 220
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Book Description
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.
