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AI Agents in Action: Build, orchestrate, and deploy autonomous multi-agent systems
AI Agents in Action: Build, orchestrate, and deploy autonomous multi-agent systems
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AI Agents in Action: Build, orchestrate, and deploy autonomous multi-agent systems
AI Agents in Action: Build, orchestrate, and deploy autonomous multi-agent systems
AI Agents in Action: Build, orchestrate, and deploy autonomous multi-agent systems
AI Agents in Action teaches you to develop and deliver LLM-based assistants and agents that can independently process information, make decisions, and learn from interactions.
AI Agents in Action: Build, orchestrate, and deploy autonomous multi-agent systems
Lambar abu: 119895901

AI Agents in Action: Build, orchestrate, and deploy autonomous multi-agent systems

89% of respondents would recommend this to a friend

Lambar abu: 119895901

XOF 53559

XOF 56894

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AI Agents in Action teaches you to develop and deliver LLM-based assistants and agents that can independently process information, make decisions, and learn from interactions.
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What Stands Out

Real-Time Insights
Leverage advanced AI algorithms to deliver real-time insights that enhance decision-making processes, empowering users to respond swiftly to shifting market dynamics.
User-Friendly Interface
Designed with simplicity in mind, the intuitive interface ensures accessibility for all skill levels, fostering seamless interaction and reducing the learning curve for new users.
Customizable Solutions
Tailor the AI capabilities to meet specific business needs with customizable features, providing flexible solutions that drive efficiency and optimize performance across diverse industries.

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Shop AI Agents in Action: Build, orchestrate, and deploy autonomous multi-agent systems online at a best price in Niger. 1633436349
  • Create LLM-powered autonomous agents and intelligent assistants tailored to your business and personal needs.From script-free customer service chatbots to fully independent agents operating seamlessly in the background, AI-powered assistants represent a breakthrough in machine intelligence. In AI Agents in Action, you'll master a proven framework for developing practical agents that handle real-world business and personal tasks. Author Micheal Lanham combines cutting-edge academic research with hands-on experience to help you: • Understand and implement AI agent behavior patterns • Design and deploy production-ready intelligent agents • Leverage the OpenAI Assistants API and complementary tools • Implement robust knowledge management and memory systems • Create self-improving agents with feedback loops • Orchestrate collaborative multi-agent systems • Enhance agents with speech and vision capabilities You won't find toy examples or fragile assistants that require constant supervision. AI Agents in Action teaches you to build trustworthy AI capable of handling high-stakes negotiations. You'll master prompt engineering to create agents with distinct personas and profiles, and develop multi-agent collaborations that thrive in unpredictable environments. Beyond just learning a new technology, you'll discover a transformative approach to problem-solving. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Most production AI systems require many orchestrated interactions between the user, AI models, and a wide variety of data sources. AI agents capture and organize these interactions into autonomous components that can process information, make decisions, and learn from interactions behind the scenes. This book will show you how to create AI agents and connect them together into powerful multi-agent systems. About the book In AI Agents in Action, you’ll learn how to build production-ready assistants, multi-agent systems, and behavioral agents. You’ll master the essential parts of an agent, including retrieval-augmented knowledge and memory, while you create multi-agent applications that can use software tools, plan tasks autonomously, and learn from experience. As you explore the many interesting examples, you’ll work with state-of-the-art tools like OpenAI Assistants API, GPT Nexus, LangChain, Prompt Flow, AutoGen, and CrewAI. What's inside • Knowledge management and memory systems • Feedback loops for continuous agent learning • Collaborative multi-agent systems • Speech and computer vision About the reader For intermediate Python programmers. About the author Micheal Lanham is a software and technology innovator with over 20 years of industry experience. He has authored books on deep learning, including Manning’s Evolutionary Deep Learning. Table of Contents 1 Introduction to agents and their world 2 Harnessing the power of large language models 3 Engaging GPT assistants 4 Exploring multi-agent systems 5 Empowering agents with actions 6 Building autonomous assistants 7 Assembling and using an agent platform 8 Understanding agent memory and knowledge 9 Mastering agent prompts with prompt flow 10 Agent reasoning and evaluation 11 Agent planning and feedback A Accessing OpenAI large language models B Python development environment
Publisher Manning Publications
Publication date March 25, 2025
Language English
Print length 344 pages
ISBN-10 1633436349
ISBN-13 978-1633436343
Item Weight 1.25 pounds (570 grams)
Dimensions 7.38 x 0.86 x 9.25 inches (18.7 x 2.2 x 23.5 cm)

Who Should Buy?

Suitable For
  • Developers

    Ideal for developers looking to implement AI agents into applications for enhanced functionality and user interaction.

  • Business Analysts

    Business analysts can leverage AI agents to analyze data trends and improve decision-making processes effectively.

  • Tech Enthusiasts

    Perfect for tech enthusiasts eager to explore AI capabilities and their real-world applications through hands-on experience.

Not Suitable For
  • Casual Users

    Not suitable for casual users seeking simple solutions without the complexity of AI implementation and management.

KWATANCEN ABUN

Kuna da wata tambaya? Yi taɗi da mu

Tambayoyi & Amsoshi Abokin Ciniki

  • Tambaya: What are AI Agents in Action?

    Amsa: AI Agents in Action refers to practical applications and demonstrations of artificial intelligence systems performing tasks autonomously or semi-autonomously. These agents are typically designed to assist users in various domains, such as customer service, data analysis, and automated decision-making. AI Agents leverage machine learning and natural language processing to enhance interaction and provide smarter solutions. For instance, a virtual assistant using AI can efficiently schedule meetings or answer queries, making it invaluable for personal productivity.
  • Tambaya: How do AI Agents improve efficiency in businesses?

    Amsa: AI Agents significantly enhance efficiency by automating repetitive tasks, thereby allowing human employees to focus on more strategic initiatives. For example, a chatbot can handle customer inquiries 24/7, providing instant responses and freeing up human agents for more complex issues. This not only leads to faster response times but also improves customer satisfaction. Companies that implement AI Agents often see increased productivity and reduced operational costs as a result.
  • Tambaya: What industries benefit the most from AI Agents?

    Amsa: Various industries are reaping significant benefits from AI Agents, particularly in sectors such as customer service, finance, healthcare, and marketing. In customer service, AI chatbots facilitate instant communication and streamline support requests. In finance, AI Agents can analyze markets and optimize investment strategies. Healthcare providers use AI for patient management and data analysis. The versatility of AI Agents means they can be tailored to meet specific needs across diverse fields.
  • Tambaya: Can AI Agents be customized for specific business needs?

    Amsa: Yes, AI Agents can be highly customized to align with specific business needs and objectives. Organizations can adjust their algorithms, workflows, and interfaces to match their operational requirements. For example, if a retail company wants to enhance its customer service, it can program its AI Agent to respond with personalized recommendations based on user purchase history. This level of customization ensures that the AI solution effectively addresses unique challenges and offers tailored user experiences.
  • Tambaya: What skills do AI Agents possess?

    Amsa: AI Agents are equipped with a variety of skills, such as natural language understanding, machine learning capabilities, and data analysis. These skills enable them to process and interpret human input, learn from interactions, and derive insights from large datasets. For instance, an AI Agent in sales can analyze customer data to identify purchasing trends and provide tailored product suggestions. This versatility allows AI Agents to adapt and perform efficiently in a range of contexts and applications.
  • Tambaya: How secure is the data processed by AI Agents?

    Amsa: Data security in AI Agents is a crucial concern, as they often handle sensitive information. Leading AI solutions implement robust security measures, including encryption and access controls, to protect data integrity and confidentiality. Additionally, adhering to data protection regulations such as GDPR ensures that user information is managed responsibly. Businesses must also consider integrating secure access protocols, making sure that their AI Agents maintain high standards of data privacy during operations.
  • Tambaya: What are the limitations of AI Agents?

    Amsa: While AI Agents are powerful tools, they are not without limitations. They may struggle with understanding complex human emotions or cultural nuances, which can lead to miscommunication. Furthermore, AI Agents require substantial training data to function effectively, and they might not perform well in scenarios that deviate from their training. For example, if a user asks a question outside the agent's programmed knowledge, it may provide irrelevant or confusing responses, highlighting the need for continuous updating and training.
  • Tambaya: How do AI Agents impact customer experience?

    Amsa: AI Agents play a transformative role in enhancing customer experience by providing prompt responses and personalized interactions. They can handle inquiries at any time, ensuring that customers receive assistance without long wait times. Moreover, through machine learning, AI Agents can learn from previous interactions, offering increasingly relevant suggestions. For instance, an AI Agent in an e-commerce setting can analyze browsing and purchase behaviors to recommend products, thereby creating a more engaging shopping experience for customers.
  • Tambaya: What technologies power AI Agents?

    Amsa: AI Agents are powered by a variety of sophisticated technologies like natural language processing (NLP), machine learning algorithms, and neural networks. NLP allows them to understand and generate human language, while machine learning enables continuous improvement in their responses based on user interactions. For instance, a virtual AI assistant can learn from past conversations to enhance its effectiveness over time. These technologies collectively ensure that AI Agents are capable of delivering intelligent and conversational experiences.
  • Tambaya: Where can I buy AI Agents in Action in Niger?

    Amsa: You can purchase AI Agents in Action through Ubuy in Niger. Ubuy offers a wide selection of AI-related products and resources, making it a reliable source for acquiring the latest innovations in AI technology. Their user-friendly interface and extensive inventory makes it easy to find the AI solutions that best fit your needs.

Expert Systems Editorial Review

  • ubuy Niger

**** The product, "AI Agents in Action," has received positive feedback from customers who are eager to engage with the material. Reviewers Consistently highlight the quality of the content, emphasizing that it introduces a wide array of use cases and examples that not only demonstrate the capabilities of AI agents but also enhance the reader's understanding of the subject matter. The structural organization of the book has been particularly praised, as it makes the content easy to digest and accessible for readers, whether they are newcomers to the field or have prior knowledge. Furthermore, readers report that they found the writing style engaging and informative, making the learning experience both enjoyable and valuable. Overall, it is evident that this book is well-received for its educational merit in the field of AI, making it a worthwhile read for anyone interested in this rapidly evolving area. **

Customer Reviews & Ratings

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Ribobi

  • Quality content with informative use cases and examples.
  • Well-organized and easy-to-read structure.
  • Engaging writing style that enhances learning.
  • Valuable resource for those interested in AI.

Fursunoni

  • Not mentioned (All reviews are positive without noted drawbacks).

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Fasaloli & Fa'idoji

  • Learn to create LLM-powered autonomous agents.
  • Develop AI assistants that adapt to business and personal needs.
  • Understand and manage AI agent behavior and decision-making.
  • Utilize OpenAI Assistants API and design multi-agent systems.
  • Implement feedback loops for continual learning.
  • Transform routine tasks with independent, intelligent agents.

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