Deep Learning — księgarnia — strona 21

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Deep Learning with TensorFlow. Explore neural networks with Python

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Practical Machine Learning Cookbook. Supervised and unsupervised machine learning simplified

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Java Data Science Cookbook. Explore the power of MLlib, DL4j, Weka, and more

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Hands-On Machine Learning with Scikit-Learn and TensorFlow. Concepts, Tools, and Techniques to Build Intelligent Systems

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Deep Learning with Hadoop. Distributed Deep Learning with Large-Scale Data

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TensorFlow Machine Learning Cookbook. Over 60 practical recipes to help you master Google's TensorFlow machine learning library

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Java for Data Science. Examine the techniques and Java tools supporting the growing field of data science

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Apache Spark for Data Science Cookbook. Solve real-world analytical problems

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Practical Machine Learning with H2O. Powerful, Scalable Techniques for Deep Learning and AI

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OpenCV: Computer Vision Projects with Python. Develop computer vision applications with OpenCV

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Julia for Data Science. high-performance computing simplified

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Mastering Predictive Analytics with Python. Exploit the power of data in your business by building advanced predictive modeling applications with Python

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Advanced Machine Learning with Python. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python

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Java Deep Learning Essentials. Unlocking the next generation of predictive power

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F# for Machine Learning Essentials. Get up and running with machine learning with F# in a fun and functional way

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Practical Machine Learning. Learn how to build Machine Learning applications to solve real-world data analysis challenges with this Machine Learning book – packed with practical tutorials

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Learning Bayesian Models with R. Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems

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Mastering OpenCV with Practical Computer Vision Projects. This is the definitive advanced tutorial for OpenCV, designed for those with basic C++ skills. The computer vision projects are divided into easily assimilated chapters with an emphasis on practica

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Programming Computer Vision with Python. Tools and algorithms for analyzing images

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