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Tag: Autoencoders

  • Generating a New Reality: From Autoencoders and Adversarial Networks to Deepfakes

    Generating a New Reality: From Autoencoders and Adversarial Networks to Deepfakes


    Price: $5.99
    (as of Dec 24,2024 22:44:33 UTC – Details)




    ASIN ‏ : ‎ B099MW4GQB
    Publisher ‏ : ‎ Apress (July 15, 2021)
    Publication date ‏ : ‎ July 15, 2021
    Language ‏ : ‎ English
    File size ‏ : ‎ 22476 KB
    Text-to-Speech ‏ : ‎ Enabled
    Screen Reader ‏ : ‎ Supported
    Enhanced typesetting ‏ : ‎ Enabled
    X-Ray ‏ : ‎ Not Enabled
    Word Wise ‏ : ‎ Not Enabled
    Print length ‏ : ‎ 433 pages


    In today’s digital age, the lines between reality and fiction are becoming increasingly blurred. With the advent of advanced technologies such as autoencoders and adversarial networks, it is now possible to create highly realistic fake videos and images known as deepfakes.

    Autoencoders are a type of artificial neural network that can learn to encode and decode data efficiently. By training an autoencoder on a set of images or videos, it can generate new, realistic-looking content that is indistinguishable from the original data.

    Adversarial networks, on the other hand, consist of two competing neural networks – a generator and a discriminator. The generator creates fake content, while the discriminator tries to distinguish between real and fake data. Through this iterative process, both networks improve their performance, resulting in highly convincing deepfakes.

    While the technology behind deepfakes is impressive, it also raises serious ethical concerns. Deepfakes have the potential to spread misinformation, manipulate public opinion, and even be used for malicious purposes such as creating fake celebrity pornographic videos.

    As we navigate this new era of digital deception, it is crucial to develop robust detection methods and educate the public about the dangers of deepfakes. By staying informed and vigilant, we can help prevent the spread of fake news and protect the integrity of our increasingly digitized world.
    #Generating #Reality #Autoencoders #Adversarial #Networks #Deepfakes

  • Learn Python Generative AI: Journey from autoencoders to transformers to large

    Learn Python Generative AI: Journey from autoencoders to transformers to large



    Learn Python Generative AI: Journey from autoencoders to transformers to large

    Price : 43.94

    Ends on : N/A

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    scale models

    In this post, we will explore the fascinating world of Python Generative AI, starting from the basics of autoencoders to the advanced models like transformers and large-scale models. Generative AI is a branch of artificial intelligence that focuses on creating new content, such as images, music, or text, based on patterns learned from existing data.

    We will begin by understanding the concept of autoencoders, which are neural network models that learn to compress and decompress data. Autoencoders are commonly used in image and text generation tasks, and we will walk through how to build and train an autoencoder using Python.

    Next, we will dive into transformers, a powerful deep learning model architecture that has revolutionized natural language processing tasks. Transformers have been used in state-of-the-art language generation models like GPT-3, and we will explore how to implement a transformer model for text generation in Python.

    Finally, we will discuss large-scale generative models, which leverage massive amounts of data and computational resources to generate high-quality content. Models like OpenAI’s DALL-E and GPT-3.5 have demonstrated the capabilities of large-scale generative AI, and we will cover how to work with these models using Python libraries.

    By the end of this journey, you will have a solid understanding of Python Generative AI and be equipped to create your own generative models using advanced techniques. Join us on this exciting learning adventure and unlock the creative potential of AI!
    #Learn #Python #Generative #Journey #autoencoders #transformers #large

  • Learn Python Generative AI: Journey from autoencoders to transformers to large language models (English Edition)

    Learn Python Generative AI: Journey from autoencoders to transformers to large language models (English Edition)


    Price: $37.95 – $26.20
    (as of Dec 17,2024 16:15:23 UTC – Details)



    Are you ready to dive into the exciting world of Python Generative AI? In our latest book, “Learn Python Generative AI: Journey from autoencoders to transformers to large language models,” we will guide you through the fundamentals of generative AI and help you master the most cutting-edge techniques in the field.

    Whether you are a beginner looking to get started with autoencoders or an experienced practitioner interested in exploring large language models like GPT-3, this book has something for everyone. With step-by-step tutorials, practical examples, and hands-on projects, you will learn how to unleash the power of generative AI using Python.

    So don’t wait any longer – join us on this exciting journey and unlock the full potential of Python Generative AI. Get your copy of “Learn Python Generative AI” today!
    #Learn #Python #Generative #Journey #autoencoders #transformers #large #language #models #English #Edition

  • Learn Python Generative AI: Journey from autoencoders to transformers to – GOOD

    Learn Python Generative AI: Journey from autoencoders to transformers to – GOOD



    Learn Python Generative AI: Journey from autoencoders to transformers to – GOOD

    Price : 24.00

    Ends on : N/A

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    Learn Python Generative AI: Journey from Autoencoders to Transformers

    In this post, we will explore the exciting world of generative artificial intelligence using Python. We will start our journey by understanding the basics of autoencoders, a type of neural network that can learn to reconstruct input data. From there, we will dive into more advanced techniques such as variational autoencoders and generative adversarial networks.

    Finally, we will explore the cutting-edge transformer architecture, which has revolutionized the field of natural language processing and image generation. By the end of this journey, you will have a solid understanding of how to implement generative AI models in Python and create your own AI-generated content.

    So buckle up and get ready to dive into the world of Python generative AI. The possibilities are endless, and the results can be truly mind-blowing. Let’s get started on this exciting journey together!
    #Learn #Python #Generative #Journey #autoencoders #transformers #GOOD

  • Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition)

    Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition)


    Price: $31.19
    (as of Dec 17,2024 13:18:00 UTC – Details)



    Are you looking to dive deep into the world of Deep Learning and AI? Look no further than our latest book, “Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn.”

    In this comprehensive guide, you will learn the fundamentals of unsupervised learning, the power of autoencoders, the importance of feature engineering, and the intricacies of time series analysis. With hands-on examples and practical applications using popular tools like TensorFlow, Keras, and scikit-learn, you will gain a solid understanding of these essential concepts in Deep Learning and AI.

    Whether you are a beginner looking to get started or an experienced practitioner looking to deepen your knowledge, this book has something for everyone. So, don’t wait any longer – grab your copy today and start your journey into the exciting world of Deep Learning and AI!
    #Essentials #Deep #Learning #Experience #Unsupervised #Learning #Autoencoders #Feature #Engineering #Time #Series #Analysis #TensorFlow #Keras #scikitlearn #English #Edition

  • Deep Learning Crash Course for Beginners with Python: Theory and Applications of Artificial Neural Networks, CNN, RNN, LSTM and Autoencoders using … Learning & Data Science for Beginners)

    Deep Learning Crash Course for Beginners with Python: Theory and Applications of Artificial Neural Networks, CNN, RNN, LSTM and Autoencoders using … Learning & Data Science for Beginners)


    Price: $24.99 – $20.50
    (as of Dec 17,2024 02:12:54 UTC – Details)



    Welcome to our Deep Learning Crash Course for Beginners with Python! In this post, we will cover the theory and applications of artificial neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), long short-term memory (LSTM) networks, and autoencoders using TensorFlow, Keras, and other popular libraries.

    Deep learning is a subset of machine learning that focuses on learning representations of data through multiple layers of neural networks. It has revolutionized many industries, from healthcare to finance to autonomous driving, and is a powerful tool for pattern recognition, natural language processing, computer vision, and many other tasks.

    In this crash course, we will start by introducing the basics of neural networks and how they work. We will then dive into more advanced topics such as CNNs for image classification, RNNs for sequential data, LSTMs for time series analysis, and autoencoders for unsupervised learning.

    Throughout the course, we will use Python as our programming language of choice, along with popular libraries like TensorFlow and Keras. We will also cover the basics of data preprocessing, model training, evaluation, and deployment.

    Whether you are a complete beginner or have some experience with machine learning, this crash course will provide you with a solid foundation in deep learning and data science. Stay tuned for our upcoming posts, where we will dive deeper into specific topics and applications of deep learning. Happy learning!
    #Deep #Learning #Crash #Beginners #Python #Theory #Applications #Artificial #Neural #Networks #CNN #RNN #LSTM #Autoencoders #Learning #Data #Science #Beginners