Tag: Implement

  • Explainable AI Recipes: Implement Solutions to Model Explainability and Interpre

    Explainable AI Recipes: Implement Solutions to Model Explainability and Interpre



    Explainable AI Recipes: Implement Solutions to Model Explainability and Interpre

    Price : 36.23 – 30.19

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    tability

    In this post, we will delve into the concept of Explainable AI (XAI) and how it can be implemented in AI models to enhance their interpretability and transparency. We will explore the importance of model explainability and how it can help build trust in AI systems. Additionally, we will provide some recipes and solutions for implementing XAI techniques in AI models.

    Stay tuned for a deep dive into the world of Explainable AI and learn how to make your AI models more transparent and understandable.
    #Explainable #Recipes #Implement #Solutions #Model #Explainability #Interpre

  • Natural Language Processing with TensorFlow – Second Edition: The definitive NLP book to implement the most sought-after machine learning models and tasks

    Natural Language Processing with TensorFlow – Second Edition: The definitive NLP book to implement the most sought-after machine learning models and tasks


    Price: $40.55
    (as of Dec 25,2024 01:59:31 UTC – Details)


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    Packt is a leading publisher of technical learning content with the ability to publish books on emerging tech faster than any other.

    Our mission is to increase the shared value of deep tech knowledge by helping tech pros put software to work.

    We help the most interesting minds and ground-breaking creators on the planet distill and share the working knowledge of their peers.

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    Publisher ‏ : ‎ Packt Publishing; 2nd ed. edition (July 29, 2022)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 514 pages
    ISBN-10 ‏ : ‎ 1838641351
    ISBN-13 ‏ : ‎ 978-1838641351
    Item Weight ‏ : ‎ 1.96 pounds
    Dimensions ‏ : ‎ 9.25 x 7.52 x 1.03 inches


    Are you interested in diving deeper into the world of Natural Language Processing (NLP) using TensorFlow? Look no further than the second edition of “Natural Language Processing with TensorFlow”! This definitive guide is packed with practical examples and cutting-edge techniques to help you implement the most sought-after machine learning models and tasks in NLP.

    Whether you’re a beginner or an experienced practitioner, this book covers everything you need to know to master NLP with TensorFlow. From text classification and sentiment analysis to machine translation and chatbot development, you’ll learn how to leverage the power of TensorFlow to solve real-world NLP problems.

    With this updated edition, you’ll also explore the latest advancements in NLP, including BERT, GPT-3, and transformer models. Plus, you’ll discover how to fine-tune pre-trained models, build custom pipelines, and deploy NLP applications in production.

    Don’t miss out on this essential resource for NLP enthusiasts and machine learning practitioners alike. Get your copy of “Natural Language Processing with TensorFlow – Second Edition” today and take your NLP skills to the next level!
    #Natural #Language #Processing #TensorFlow #Edition #definitive #NLP #book #implement #soughtafter #machine #learning #models #tasks

  • S.M.A.R.T. AI for Business: Save Time and Increase Profits with Personalized Marketing Strategies, Effective Recruiting Tactics, and Easy to Implement Chatbot Technology

    S.M.A.R.T. AI for Business: Save Time and Increase Profits with Personalized Marketing Strategies, Effective Recruiting Tactics, and Easy to Implement Chatbot Technology


    Price: $0.99
    (as of Dec 24,2024 23:44:12 UTC – Details)




    ASIN ‏ : ‎ B0DCGH9DQN
    Publication date ‏ : ‎ August 8, 2024
    Language ‏ : ‎ English
    File size ‏ : ‎ 2662 KB
    Text-to-Speech ‏ : ‎ Enabled
    Screen Reader ‏ : ‎ Supported
    Enhanced typesetting ‏ : ‎ Enabled
    X-Ray ‏ : ‎ Not Enabled
    Word Wise ‏ : ‎ Not Enabled
    Print length ‏ : ‎ 226 pages
    Page numbers source ISBN ‏ : ‎ B0DD6TP3FT

    Customers say

    Customers find the book helpful for getting into an AI mindset with its practical approach and real-world applications. They describe it as a straightforward, concise, and easy-to-follow guide that helps them learn quickly. The book is great for business owners looking to understand AI’s potential without getting lost, and perfect for busy entrepreneurs looking to improve their current business plan.

    AI-generated from the text of customer reviews


    In today’s fast-paced business world, time is money. That’s why more and more companies are turning to S.M.A.R.T. AI technology to streamline their operations, save time, and increase profits.

    S.M.A.R.T. AI stands for Specific, Measurable, Achievable, Relevant, and Time-bound. By utilizing this technology, businesses can create personalized marketing strategies that target specific customer segments, measure the effectiveness of their campaigns, achieve their marketing goals, and increase their profits in a timely manner.

    One of the key benefits of S.M.A.R.T. AI technology is its ability to personalize marketing strategies for individual customers. By analyzing customer data and behavior, businesses can create targeted campaigns that speak directly to the needs and interests of their target audience. This personalized approach not only increases customer engagement but also boosts conversion rates and sales.

    In addition to personalized marketing strategies, S.M.A.R.T. AI technology can also be used to improve recruiting tactics. By automating the screening and interviewing process, businesses can save time and resources, while also ensuring that they hire the best candidates for the job. This not only improves employee retention but also helps businesses stay competitive in the marketplace.

    Another key aspect of S.M.A.R.T. AI technology is its chatbot capabilities. By implementing chatbots on their websites or social media platforms, businesses can provide 24/7 customer support, answer frequently asked questions, and even assist with sales transactions. This not only improves customer satisfaction but also frees up employees to focus on more strategic tasks.

    Overall, S.M.A.R.T. AI technology is revolutionizing the way businesses operate. By saving time, increasing profits, and improving customer satisfaction, this technology is a game-changer for companies looking to stay ahead of the competition. So why wait? Embrace S.M.A.R.T. AI technology today and take your business to the next level!
    #S.M.A.R.T #Business #Save #Time #Increase #Profits #Personalized #Marketing #Strategies #Effective #Recruiting #Tactics #Easy #Implement #Chatbot #Technology

  • Raspberry Pi Computer Vision Programming: Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3, 2nd Edition

    Raspberry Pi Computer Vision Programming: Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3, 2nd Edition


    Price: $17.97
    (as of Dec 24,2024 16:33:02 UTC – Details)




    ASIN ‏ : ‎ B085P1HWPM
    Publisher ‏ : ‎ Packt Publishing; 2nd edition (June 29, 2020)
    Publication date ‏ : ‎ June 29, 2020
    Language ‏ : ‎ English
    File size ‏ : ‎ 25796 KB
    Text-to-Speech ‏ : ‎ Enabled
    Screen Reader ‏ : ‎ Supported
    Enhanced typesetting ‏ : ‎ Enabled
    X-Ray ‏ : ‎ Not Enabled
    Word Wise ‏ : ‎ Not Enabled
    Print length ‏ : ‎ 306 pages


    If you’re looking to dive into the world of computer vision programming using Raspberry Pi, OpenCV, and Python 3, then the newly released 2nd edition of “Raspberry Pi Computer Vision Programming” is the perfect guide for you.

    This comprehensive book covers everything you need to know to design and implement computer vision applications on the popular Raspberry Pi platform. From setting up your Raspberry Pi and installing OpenCV to creating your own image processing and object detection programs, this book walks you through the entire process step by step.

    With practical examples and hands-on projects, you’ll learn how to harness the power of Raspberry Pi and OpenCV to build real-world computer vision applications. Whether you’re a beginner looking to get started with computer vision programming or a seasoned developer looking to expand your skills, this book has something for everyone.

    So grab your Raspberry Pi, fire up your Python interpreter, and get ready to unlock the full potential of computer vision programming with “Raspberry Pi Computer Vision Programming, 2nd Edition”.
    #Raspberry #Computer #Vision #Programming #Design #implement #computer #vision #applications #Raspberry #OpenCV #Python #2nd #Edition

  • Modern Computer Vision with PyTorch: Explore deep learning concepts and implement over 50 real-world image applications

    Modern Computer Vision with PyTorch: Explore deep learning concepts and implement over 50 real-world image applications


    Price: $65.99 – $61.17
    (as of Dec 24,2024 10:47:26 UTC – Details)




    Publisher ‏ : ‎ Packt Publishing (November 27, 2020)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 824 pages
    ISBN-10 ‏ : ‎ 1839213477
    ISBN-13 ‏ : ‎ 978-1839213472
    Item Weight ‏ : ‎ 3.1 pounds
    Dimensions ‏ : ‎ 9.25 x 7.52 x 1.69 inches


    In this post, we will delve into the world of modern Computer Vision with PyTorch, a powerful deep learning framework. We will explore key concepts in deep learning and demonstrate how to implement over 50 real-world image applications using PyTorch.

    Computer Vision is a field of artificial intelligence that enables computers to interpret and understand the visual world. With the advancements in deep learning and the availability of high-performance computing resources, Computer Vision has seen incredible progress in recent years.

    PyTorch is a popular open-source deep learning framework that provides flexible tools and libraries for building and training deep neural networks. With PyTorch, you can easily implement complex deep learning models for Computer Vision tasks, such as image classification, object detection, image segmentation, and more.

    In this post, we will cover a wide range of topics in modern Computer Vision, including:

    – Introduction to deep learning and neural networks
    – Convolutional Neural Networks (CNNs) for image classification
    – Transfer learning and fine-tuning pre-trained models
    – Object detection using Faster R-CNN and YOLO
    – Semantic segmentation with U-Net and DeepLabv3
    – Generative Adversarial Networks (GANs) for image synthesis
    – And much more!

    Throughout the post, we will provide hands-on examples and code snippets to help you understand and implement these concepts in PyTorch. By the end of this post, you will have a solid understanding of modern Computer Vision techniques and be able to apply them to a wide range of real-world image applications.

    So, if you are interested in exploring the cutting-edge of Computer Vision with PyTorch, stay tuned for our upcoming posts!
    #Modern #Computer #Vision #PyTorch #Explore #deep #learning #concepts #implement #realworld #image #applications

  • The Machine Learning and Data Science Bible: [5 in 1] Master the World of Data Science by Learning How to Design, Monitor, and Implement Reliable ML Systems | With Real-World Applications Examples

    The Machine Learning and Data Science Bible: [5 in 1] Master the World of Data Science by Learning How to Design, Monitor, and Implement Reliable ML Systems | With Real-World Applications Examples


    Price: $17.97
    (as of Dec 24,2024 10:05:23 UTC – Details)




    Publisher ‏ : ‎ Rick C. Worley (October 2, 2024)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 213 pages
    ISBN-10 ‏ : ‎ 1917549075
    ISBN-13 ‏ : ‎ 978-1917549073
    Item Weight ‏ : ‎ 1.39 pounds
    Dimensions ‏ : ‎ 8.5 x 0.48 x 11 inches


    Are you looking to master the world of data science and machine learning? Look no further than “The Machine Learning and Data Science Bible: [5 in 1] Master the World of Data Science by Learning How to Design, Monitor, and Implement Reliable ML Systems”. This comprehensive guide covers everything you need to know to become an expert in the field.

    With real-world application examples and practical exercises, this book will help you understand the principles behind machine learning and data science, as well as how to design, monitor, and implement reliable ML systems. Whether you’re a beginner or an experienced practitioner, this book has something for everyone.

    So why wait? Start your journey to becoming a data science and machine learning expert today with “The Machine Learning and Data Science Bible: [5 in 1] Master the World of Data Science by Learning How to Design, Monitor, and Implement Reliable ML Systems”.
    #Machine #Learning #Data #Science #Bible #Master #World #Data #Science #Learning #Design #Monitor #Implement #Reliable #Systems #RealWorld #Applications #Examples

  • Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python

    Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python


    Price: $54.07
    (as of Dec 24,2024 08:57:57 UTC – Details)



    Are you tired of black-box AI models that provide no insight into how they make decisions? Look no further! In this post, we will explore Explainable AI (XAI) recipes that allow you to implement solutions for model explainability and interpretability using Python.

    Explainable AI has become increasingly important in the field of artificial intelligence, as stakeholders demand transparency and accountability from AI systems. By understanding how a model arrives at its predictions, we can trust its decisions and identify potential biases or errors.

    In this post, we will cover a variety of techniques and tools that you can use to make your AI models more explainable. From feature importance analysis to model-agnostic methods like LIME and SHAP, we will explore different approaches to understanding and interpreting your models.

    By the end of this post, you will have a solid understanding of how to implement solutions for model explainability and interpretability in Python. So, if you’re ready to demystify your AI models and gain valuable insights into their decision-making processes, keep reading!
    #Explainable #Recipes #Implement #Solutions #Model #Explainability #Interpretability #Python

  • Hands-On Generative Adversarial Networks with PyTorch 1.x: Implement next-generation neural networks to build powerful GAN models using Python

    Hands-On Generative Adversarial Networks with PyTorch 1.x: Implement next-generation neural networks to build powerful GAN models using Python


    Price: $51.29
    (as of Dec 24,2024 05:33:14 UTC – Details)



    Are you interested in diving into the world of Generative Adversarial Networks (GANs) and harnessing the power of PyTorch 1.x to create cutting-edge neural networks? Look no further than our hands-on workshop on implementing next-generation GAN models using Python!

    In this workshop, you will learn how to leverage the capabilities of PyTorch 1.x to build powerful GAN models that can generate realistic images, texts, and more. You will gain a deep understanding of how GANs work, how to train and evaluate them effectively, and how to apply them to real-world problems.

    Whether you are a beginner looking to explore the exciting field of GANs or an experienced practitioner seeking to enhance your skills, this workshop is perfect for you. Join us and unlock the potential of GANs with PyTorch 1.x!

    Stay tuned for more details on dates, registration, and workshop materials. Don’t miss this opportunity to level up your deep learning skills and create cutting-edge AI applications with GANs! #GANs #PyTorch #DeepLearning #AI #Python
    #HandsOn #Generative #Adversarial #Networks #PyTorch #1.x #Implement #nextgeneration #neural #networks #build #powerful #GAN #models #Python

  • Responsible AI: Implement an Ethical Approach in your Organization

    Responsible AI: Implement an Ethical Approach in your Organization



    Responsible AI: Implement an Ethical Approach in your Organization

    Price : 31.00

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    In today’s rapidly advancing technological landscape, the use of artificial intelligence (AI) is becoming more prevalent in various industries. However, with great power comes great responsibility. It is imperative for organizations to implement an ethical approach when developing and deploying AI systems to ensure that they are used in a responsible and fair manner.

    Here are some key steps that organizations can take to ensure the responsible use of AI:

    1. Establish clear guidelines and principles: Organizations should develop a set of ethical guidelines and principles that outline the values and norms that govern the development and use of AI within the organization. These guidelines should be communicated to all employees and stakeholders to ensure that everyone is aware of the ethical standards that must be upheld.

    2. Prioritize transparency and accountability: Organizations should be transparent about how AI systems are being used and the data that is being collected and utilized. They should also establish mechanisms for accountability and oversight to ensure that any potential biases or ethical concerns are addressed promptly.

    3. Ensure fairness and inclusivity: Organizations should strive to create AI systems that are fair and inclusive, taking into account the diverse needs and perspectives of all stakeholders. This includes ensuring that AI systems do not perpetuate or exacerbate existing biases or discrimination.

    4. Conduct regular ethical audits: Organizations should regularly conduct ethical audits of their AI systems to assess their impact on society and identify any potential ethical risks or concerns. These audits should be conducted by independent third parties to ensure objectivity and impartiality.

    5. Invest in ethical AI training: Organizations should invest in training programs to educate employees about the ethical considerations and implications of AI technology. This will help employees make informed decisions and ensure that AI systems are developed and used in a responsible manner.

    By implementing an ethical approach to AI within their organizations, companies can build trust with their customers, employees, and stakeholders, while also contributing to a more ethical and inclusive society. Responsible AI is not just a trend – it is a necessity for organizations that want to thrive in the digital age.
    #Responsible #Implement #Ethical #Approach #Organization

  • Federated Learning with Python: Design and implement a federated learning system and develop applications using existing frameworks

    Federated Learning with Python: Design and implement a federated learning system and develop applications using existing frameworks


    Price: $46.99
    (as of Dec 24,2024 02:50:46 UTC – Details)


    Customers say

    Customers find the book provides an accessible explanation of complex federated learning concepts, providing guidance on real-world implementations and examples across industries like healthcare and finance. They find it useful and interesting for both machine learning practitioners and leaders in AI-driven companies. The practical examples and code snippets are appreciated.

    AI-generated from the text of customer reviews


    Federated Learning with Python: Design and implement a federated learning system and develop applications using existing frameworks

    Federated learning is a decentralized machine learning approach where multiple clients collaborate to train a global model without sharing their data. This enables privacy-preserving machine learning and allows for training models on sensitive data without compromising user privacy.

    In this post, we will explore how to design and implement a federated learning system using Python. We will also discuss how to develop applications using existing frameworks such as TensorFlow Federated and PySyft.

    To get started with federated learning, you will need to set up a server-client architecture where the server coordinates the training process and aggregates model updates from the clients. The clients, on the other hand, train the model locally on their own data and send the updated model parameters to the server.

    To implement this architecture in Python, you can use frameworks like TensorFlow Federated, which provides high-level APIs for federated learning. Alternatively, you can use PySyft, a privacy-preserving deep learning framework that enables secure multi-party computation.

    Once you have set up the federated learning system, you can develop applications that leverage this technology for various use cases such as healthcare, finance, and IoT. For example, you can train a predictive model on medical data from different hospitals without sharing patient information, or you can build a fraud detection system that learns from multiple banks’ transaction data without compromising customer privacy.

    Overall, federated learning is a powerful technique that enables collaborative machine learning while preserving data privacy. By designing and implementing a federated learning system in Python and developing applications using existing frameworks, you can unlock the potential of this technology for a wide range of applications.
    #Federated #Learning #Python #Design #implement #federated #learning #system #develop #applications #existing #frameworks

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