Predictive analytics with TensorFlow /

"Predictive analytics discovers hidden patterns in structured and unstructured data for automated decision-making in business intelligence. This course will help you build, tune, and deploy predictive models with TensorFlow in three main divisions. The first division covers linear algebra, stat...

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Bibliographic Details
Online Access: Full text (MCPHS users only)
Main Author: Karim, Md. Rezaul (Author)
Format: Electronic Video
Language:English
Published: [Place of publication not identified] : Packt Publishing, 2018
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Summary:"Predictive analytics discovers hidden patterns in structured and unstructured data for automated decision-making in business intelligence. This course will help you build, tune, and deploy predictive models with TensorFlow in three main divisions. The first division covers linear algebra, statistics, and probability theory for predictive modeling. The second division covers developing predictive models via supervised (classification and regression) and unsupervised (clustering) algorithms. It then explains how to develop predictive models for NLP and covers reinforcement learning algorithms. Lastly, this division covers developing a factorization machine-based recommendation system. The third division covers deep learning architectures for advanced predictive analytics, including deep neural networks and recurrent neural networks for high-dimensional and sequence data. Finally, you'll use convolutional neural networks for predictive modeling for emotion recognition, image classification, and sentiment analysis."--Resource description page
Item Description:Title from resource description page (Safari, viewed October 10, 2018).
Physical Description:1 online resource (1 streaming video file (5 hr., 21 min., 15 sec.))