applied deep learning python de galea alex (16 résultats)

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Paperback. Etat : new. Paperback. A hands-on guide to deep learning thats filled with intuitive explanations and engaging practical examplesKey FeaturesDesigned to iteratively develop the skills of Python users who dont have a data science backgroundCovers the key foundational concepts youll need to know when building deep learning systemsFull of step-by-step exercises and activities to help build the skills that you need for the real-worldBook DescriptionTaking an approach that uses the latest developments in the Python ecosystem, youll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. Well explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. Its okay if these terms seem overwhelming; well show you how to put them to work.Well build upon our classification coverage by taking a quick look at ethical web scraping and interactive visualizations to help you professionally gather and present your analysis. Its after this that we start building out our keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data.By guiding you through a trained neural network, well explore common deep learning network architectures (convolutional, recurrent, generative adversarial) and branch out into deep reinforcement learning before we dive into model optimization and evaluation. Well do all of this whilst working on a production-ready web application that combines Tensorflow and Keras to produce a meaningful user-friendly result, leaving you with all the skills you need to tackle and develop your own real-world deep learning projects confidently and effectively.What you will learnDiscover how you can assemble and clean your very own datasetsDevelop a tailored machine learning classification strategyBuild, train and enhance your own models to solve unique problemsWork with production-ready frameworks like Tensorflow and KerasExplain how neural networks operate in clear and simple termsUnderstand how to deploy your predictions to the webWho this book is forIf you're a Python programmer stepping into the world of data science, this is the ideal way to get started. Getting started with data science can be overwhelming, even for experienced developers. In this two-part, hands-on book well show you how to apply your existing understanding of the Python language to this new and exciting field thats full of new opportunities (and high expectations)! Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Etat : New. Getting started with data science can be overwhelming, even for experienced developers. In this two-part, hands-on book we ll show you how to apply your existing understanding of the Python language to this new and exciting field that s full of new opportun.

Paperback. Etat : new. Paperback. A hands-on guide to deep learning thats filled with intuitive explanations and engaging practical examplesKey FeaturesDesigned to iteratively develop the skills of Python users who dont have a data science backgroundCovers the key foundational concepts youll need to know when building deep learning systemsFull of step-by-step exercises and activities to help build the skills that you need for the real-worldBook DescriptionTaking an approach that uses the latest developments in the Python ecosystem, youll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. Well explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. Its okay if these terms seem overwhelming; well show you how to put them to work.Well build upon our classification coverage by taking a quick look at ethical web scraping and interactive visualizations to help you professionally gather and present your analysis. Its after this that we start building out our keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data.By guiding you through a trained neural network, well explore common deep learning network architectures (convolutional, recurrent, generative adversarial) and branch out into deep reinforcement learning before we dive into model optimization and evaluation. Well do all of this whilst working on a production-ready web application that combines Tensorflow and Keras to produce a meaningful user-friendly result, leaving you with all the skills you need to tackle and develop your own real-world deep learning projects confidently and effectively.What you will learnDiscover how you can assemble and clean your very own datasetsDevelop a tailored machine learning classification strategyBuild, train and enhance your own models to solve unique problemsWork with production-ready frameworks like Tensorflow and KerasExplain how neural networks operate in clear and simple termsUnderstand how to deploy your predictions to the webWho this book is forIf you're a Python programmer stepping into the world of data science, this is the ideal way to get started. Getting started with data science can be overwhelming, even for experienced developers. In this two-part, hands-on book well show you how to apply your existing understanding of the Python language to this new and exciting field thats full of new opportunities (and high expectations)! Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Taschenbuch. Etat : Neu. Applied Deep Learning with Python | Alex Galea (u. a.) | Taschenbuch | Englisch | 2018 | Packt Publishing | EAN 9781789804744 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

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