Applied Unsupervised Learning with Python: Discover hidden patterns and relationships in unstructured data with Python

Author:   Benjamin Johnston ,  Aaron Jones ,  Christopher Kruger
Publisher:   Packt Publishing Limited
ISBN:  

9781789952292


Pages:   482
Publication Date:   28 May 2019
Format:   Paperback
Availability:   In stock   Availability explained
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Applied Unsupervised Learning with Python: Discover hidden patterns and relationships in unstructured data with Python


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Author:   Benjamin Johnston ,  Aaron Jones ,  Christopher Kruger
Publisher:   Packt Publishing Limited
Imprint:   Packt Publishing Limited
ISBN:  

9781789952292


ISBN 10:   1789952298
Pages:   482
Publication Date:   28 May 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

Table of Contents Introduction to Clustering Hierarchical Clustering Neighborhood Approaches and DBSCAN An Introduction to Dimensionality Reduction and PCA Autoencoders t-Distributed Stochastic Neighbor Embedding (t-SNE) Topic Modeling Market Basket Analysis Hotspot Analysis

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Author Information

Benjamin Johnston is a senior data scientist for one of the world's leading data-driven medtech companies and is involved in the development of innovative digital solutions throughout the entire product development pathway, from problem definition, to solution research and development, through to final deployment. He is currently completing his PhD in machine learning, specializing in image processing and deep convolutional neural networks. He has more than 10 years' experience in medical device design and development, working in a variety of technical roles and holds first-class honors bachelor's degrees in both engineering and medical science from the University of Sydney, Australia. Aaron Jones is a full-time Senior Data Scientist and consultant. He has built models and data products while working in retail, media, and environmental science. Aaron is based in Seattle, Washington and has a particular interest in clustering algorithms, natural language processing, and Bayesian statistics. Christopher Kruger is a practicing data scientist and AI researcher. He has managed applied machine learning projects across multiple industries while mentoring junior team members on best practices. His primary focus is on pushing both business practicality as well as academic rigor in every project. Chris is currently developing research in the computer vision space.

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