Learn data science best practices.

 

Saras YagnavajhalaJanuary 7, 2019

Making the Case for Centralized Data Science

Oracle Hospitality Senior Director of Data Science Strategy Saras Yagnavajhala shares how a centralized approach to data science can help break organizational silos and drive measurable and scalable...
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John MillerDecember 20, 2018

How to Make Sure Your Machine Learning Model Holds Up In Court

Consider these tips to help improve the odds that your machine learning model will be used in a business setting.
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Viji KrishnamurthyDecember 19, 2018

3 Features That Will Keep Your IoT Initiative From Failing

Oracle Director of Product Management Viji Krishnamurthy covers the key features of a successful IoT project.
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Quan NguyenDecember 17, 2018

Asynchronous Programming in Python for Web Scraping

Data Scientist Quan Nguyen provides a thorough explanation of asynchronous programming in this tutorial, which illustrates the basics through a variety of examples. Follow along to learn how to build...
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Vaibhav AparimitDecember 13, 2018

Blockchain Technology for Patient Healthcare Data

Healthcare tech startup Director of Product Management Vaibhav Aparimit shares how blockchain can reduce healthcare costs, lend more transparency to sharing patient data, and do social good.
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Nikolay SavinDecember 12, 2018

AI for Retail Price Optimization: How to Get Started

Competera Head of Products Nikolay Savin gives his tips on how to start using artificial intelligence for retail price optimization.
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Nate KlynDecember 10, 2018

An Oracle Data Science Case Study in Telecom

Oracle Data Cloud Senior Data Scientist Nate Klyn shares a solution his team developed to help telecom and mobile device manufacturers better identify prospects for advertising campaigns.
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Ben LevineDecember 6, 2018

Character-Based Neural Networks for NLP in the Real World

Oracle Principal Software Engineer Ben Levine presents character-based approaches for real-world text classification problems.
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Michael PenroseDecember 5, 2018

Not Just Machine Learning: 3 Lessons Learned Working with Credit Risk Datasets

IT Consultant Michael Penrose goes over three things he learned from using credit risk datasets for automated testing and predictive modeling.
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Dylan StoreyDecember 3, 2018

Random Forests, Decision Trees, and Ensemble Methods Explained

Data scientist Dylan Storey goes over how to implement a random forest from the ground up as well as how to train, make a prediction, and compare a random forest to a decision tree.
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