Monetizing Machine Learning

Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud

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Éditeur :

Apress

Paru le : 2018-09-12

Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book—Amazon, Microsoft, Google, and PythonAnywhere. You will work through a series of common Pyth...
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À propos


Éditeur

Collection
n.c

Parution
2018-09-12

Pages
482 pages

EAN papier
9781484238721

Auteur(s) du livre


Manuel Amunategui has decades of professional experience in programming, data science, and creating end-to-end solutions for customers in various industries. He sees informational and educational gaps in the industry. He has been fortunate to work with software at Microsoft, in finance on Wall Street, in research at one of the largest health systems in the US, and now as VP of Data Science at SpringML, a Google Cloud and Salesforce preferred partner. He understands what it takes to start new careers and new businesses. Since 2013, he has been advocating for data science through blogs, vlogs, and educational material. He has grown and curated various highly focused and niche social media channels, including a YouTube channel with 60 videos and 350k views and a very popular applied data science blog. His teaching perspective is about welcoming any new comer with a desire to learn, creating material to quickly overcome learning curves, and demonstrating through clear narrative and practical examples that it is never as hard as most people think. Mehdi Roopaei, PhD, is a postdoctoral fellow at Open Cloud Institute of University of Texas at San Antonio, with a research focus on data-driven decision-making systems. He has 12 years of experience in teaching at the university level, more than 980 citations for peer-reviewed publications, and two published books. His focus is on cloud machine learning, data analytics, and the AI-Thinking platform (proposed at HICSS51).

Caractéristiques détaillées - droits

EAN PDF
9781484238738
Prix
78,87 €
Nombre pages copiables
4
Nombre pages imprimables
48
Taille du fichier
22938 Ko
EAN EPUB
9781484238738
Prix
78,87 €
Nombre pages copiables
4
Nombre pages imprimables
48
Taille du fichier
37171 Ko

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