{"product_id":"learning-algorithms-for-internet-of-things-applying-python-tools-to-improve-data-collection-use-for-system-performance-9798868805295","title":"Learning Algorithms for Internet of Things: Applying Python Tools to Improve Data Collection Use for System Performance","description":"\u003cp\u003eThe advent of Internet of Things (IoT) has paved the way for sensing the environment and smartly responding. This can be further improved by enabling intelligence to the system with the support of machine learning and deep learning techniques. This book describes learning algorithms that can be applied to IoT-based, real-time applications and improve the utilization of data collected and the overall performance of the system.\u003c\/p\u003e \u003cp\u003eMany societal challenges and problems can be resolved using a better amalgamation of IoT and learning algorithms. \"Smartness\" is the buzzword that is realized only with the help of learning algorithms. In addition, it supports researchers with code snippets that focus on the implementation and performance of learning algorithms on IoT based applications such as healthcare, agriculture, transportation, etc. These snippets include Python packages such as Scipy, Scikit-learn, Theano, TensorFlow, Keras, PyTorch, and more.\u003c\/p\u003e \u003cp\u003e\u003cem\u003eLearning Algorithms for Internet of Things \u003c\/em\u003eprovides you with an easier way to understand the purpose and application of learning algorithms on IoT.\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eWhat you'll Learn\u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eSupervised algorithms such as Regression and Classification.\u003c\/li\u003e \u003cli\u003eUnsupervised algorithms, like K-means clustering, KNN, hierarchical clustering, principal component analysis, and more.\u003c\/li\u003e \u003cli\u003eArtificial neural networks for IoT (architecture, feedback, feed-forward, unsupervised).\u003c\/li\u003e \u003cli\u003eConvolutional neural networks for IoT (general, LeNet, AlexNet, VGGNet, GoogLeNet, etc.).\u003c\/li\u003e \u003cli\u003eOptimization methods, such as gradient descent, stochastic gradient descent, Adagrad, AdaDelta, and IoT optimization.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cstrong\u003eWho This Book Is For \u003c\/strong\u003e\u003c\/p\u003e \u003cp\u003eStudents interested in learning algorithms and their implementations, as well as researchers in IoT looking to extend their work with learning algorithms\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Apress\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 12\/20\/2024\u003cbr\u003e\u003cb\u003eISBN:\u003c\/b\u003e 9798868805295\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 299\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.99lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.21h x 6.14w x 0.67d","brand":"G. R. Kanagachidambaresan, N. Bharathi","offers":[{"title":"Default Title","offer_id":45396533543093,"sku":"9798868805295","price":38.24,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0473\/0804\/6492\/files\/img_73774dcc-372a-4fd6-b276-974cf41a2b01.jpg?v=1747750226","url":"https:\/\/pastforward.org\/products\/learning-algorithms-for-internet-of-things-applying-python-tools-to-improve-data-collection-use-for-system-performance-9798868805295","provider":"Past Forward","version":"1.0","type":"link"}