Categorias

Pluralsight

10 dias de trial grátis

$ 26.00/mês

+ todos os cursos

Descrição do Curso

This course covers the finer points of building such models as well the logistic regression, nearest-neighbor methods, and metrics for evaluating classifiers such as accuracy, precision, and recall.TensorFlow is a great way to implement powerful classification models such as Convolutional Neural Networks and Recurrent Neural Networks. In this course, Building Classification Models with TensorFlow, you'll learn a variety of different machine learning techniques to build classification models. First, you'll begin by covering metrics, such as accuracy, precision, and recall that can be used to evaluate classification models and determine which metric is the right one for your use case. Next, you'll delve into more traditional machine learning techniques such as logistic regression and the k-nearest neighbor methods for classification. Finally, you'll discover how to implement more powerful classification models such as Convolutional Neural Networks and Recurrent Neural Networks. By the end of this course, you'll have a better understanding of how to build classification models with TensorFlow.

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Detalhes do Curso

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kk,gl,bs,fr,mk

Janani Ravi

Rítmo flexível

Intermediário

3 horas

Pluralsight

10 dias de trial grátis

$ 26.00/mês

+ todos os cursos

Detalhes do Curso

en

kk,gl,bs,fr,mk

Janani Ravi

Rítmo flexível

Intermediário

3 horas

Descrição do Curso

This course covers the finer points of building such models as well the logistic regression, nearest-neighbor methods, and metrics for evaluating classifiers such as accuracy, precision, and recall.TensorFlow is a great way to implement powerful classification models such as Convolutional Neural Networks and Recurrent Neural Networks. In this course, Building Classification Models with TensorFlow, you'll learn a variety of different machine learning techniques to build classification models. First, you'll begin by covering metrics, such as accuracy, precision, and recall that can be used to evaluate classification models and determine which metric is the right one for your use case. Next, you'll delve into more traditional machine learning techniques such as logistic regression and the k-nearest neighbor methods for classification. Finally, you'll discover how to implement more powerful classification models such as Convolutional Neural Networks and Recurrent Neural Networks. By the end of this course, you'll have a better understanding of how to build classification models with TensorFlow.

Tags Relacionadas