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Use of Machine Learning to Make Money on Android Monetization

Smart Data Collective

As we said in the past, big data and machine learning technology can be invaluable in the realm of software development. Machine learning technology has become a lot more important in the app development profession. Machine learning can be surprisingly useful when it comes to monetizing apps.

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Running Code and Failing Models

DataRobot

Machine learning is a glass cannon. The promise and power of AI lead many researchers to gloss over the ways in which things can go wrong when building and operationalizing machine learning models. As a data scientist, one of my passions is to reproduce research papers as a learning exercise.

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Bringing an AI Product to Market

O'Reilly on Data

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Agreeing on metrics.

Marketing 363
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Conversational AI: Design & Build a Contextual Assistant – Part 1

CDW Research Hub

For instance, a level 1 travel bot can provide a link for you to book travel. Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language. I want to book a trip. Can you book a trip for me? ## intent:inform.

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Moving Beyond CTR: Better Recommendations Through Human Evaluation

Edwin Chen

I'm a big fan of man-in-the-machine techniques , so to get around this problem, I'm going to talk about a human evaluation approach to measuring the performance of personalization and discovery products. In particular, I'll use the example of related book suggestions on Amazon as I walk through the rest of this post.

Metrics 79
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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

Much has been written about struggles of deploying machine learning projects to production. This approach has worked well for software development, so it is reasonable to assume that it could address struggles related to deploying machine learning in production too. However, the concept is quite abstract.

IT 351