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Monetizing Machine Learning Download pdf

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Monetizing Machine Learning 
Picture Of The Book:
Free Download Monetizing Machine Learning pdf
Monetizing Machine Learning 
About The Book:

You will work through a progression of regular Python issues in information science in developing request of intricacy. The commonsense undertakings introduced right now straightforward and clear and can be utilized as formats to begin numerous other task types. You will figure out how to make a web application about numerical or straight out expectations, comprehend content investigation, make ground-breaking and intuitive introductions, limit information get to administration, and exploit web modules to acknowledge charge card installments and gifts. You will get your tasks in the hands of the world in a matter of moments.

Contents Of The Book:

Chapter 1: Introduction to Serverless Technologies.
Chapter 2: Client-Side Intelligence Using Regression Coefficients on Azure.
Chapter 3: Real-Time Intelligence with Logistic Regression on GCP.
Chapter 4: Pretrained Intelligence with Gradient Boosting Machine on AWS.
Chapter 5: Case Study Part 1: Supporting Both Web and Mobile Browsers.
Chapter 6: Displaying Predictions with Google Maps on Azure.
Chapter 7: Forecasting with Naive Bayes and OpenWeather on AWS.
Chapter 8: Interactive Drawing Canvas and Digit Predictions Using TensorFlow on GCP.
Chapter 9: Case Study Part 2: Displaying Dynamic Charts.
Chapter 10: Recommending with Singular Value Decomposition on GCP.
Chapter 11: Simplifying Complex Concepts with NLP and Visualization on Azure.
Chapter 12: Case Study Part 3: Enriching Content with Fundamental Financial Information.
Chapter 13: Google Analytics.
Chapter 14: A/B Testing on PythonAnywhere and MySQL.
Chapter 15: From Visitor to Subscriber.
Chapter 16: Case Study Part 4: Building a Subscription Paywall with Memberful.
Chapter 17: Conclusion.

Information About The Book:

Title: Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud.
Language: English.
Size: 23.0 Mb.
Pages: 510.
Format: Pdf.
Year: 2018.
Edition: 1.
Author: Manuel Amunategui.
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