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    1. Data och IT
    2. Systemvetenskap och AI

    Hands-On Meta Learning with Python

    Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow

    AvSudharsan Ravichandiran

    Häftad, Engelska, 2018

    584 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Explore a diverse set of meta-learning algorithms and techniques to enable human-like cognition for your machine learning models using various Python frameworksKey FeaturesUnderstand the foundations of meta learning algorithmsExplore practical examples to explore various one-shot learning algorithms with its applications in TensorFlowMaster state of the art meta learning algorithms like MAML, reptile, meta SGDBook DescriptionMeta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster.Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning.By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models.What you will learnUnderstand the basics of meta learning methods, algorithms, and typesBuild voice and face recognition models using a siamese networkLearn the prototypical network along with its variantsBuild relation networks and matching networks from scratchImplement MAML and Reptile algorithms from scratch in PythonWork through imitation learning and adversarial meta learningExplore task agnostic meta learning and deep meta learningWho this book is forHands-On Meta Learning with Python is for machine learning enthusiasts, AI researchers, and data scientists who want to explore meta learning as an advanced approach for training machine learning models. Working knowledge of machine learning concepts and Python programming is necessary.

    Produktinformation

    • Utgivningsdatum:2018-12-31
    • Mått:191 x 235 x 13 mm
    • Vikt:431 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:226
    • Förlag:Packt Publishing Limited
    • ISBN:9781789534207

    Utforska kategorier

    • Systemvetenskap och AI inom Data och IT

    Mer om författaren

    Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.

    Innehållsförteckning

    • Table of ContentsIntroduction to Meta LearningFace and Audio Recognition using Siamese NetworkPrototypical Network and its variantsBuilding Matching and Relation Network using TensorflowMemory Augmented NetworksMAML and its variantsMeta-SGD and Reptile ALgorithmGradient Agreement as an Optimization ObjectiveRecent Advancements and Next Steps