Remove 2019 Remove Experimentation Remove Interactive Remove Machine Learning
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6 trends framing the state of AI and ML

O'Reilly on Data

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. Unsupervised learning is growing. Growth in ML and AI is unabated.

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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

It is also important to have a strong test and learn culture to encourage rapid experimentation. The use of newer techniques, especially Machine Learning and Deep Learning, including RNNs and LSTMs, have high applicability in time series forecasting. What are you most looking forward to about CDAOI Insurance 2019?

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Customer Experience and Emerging Technologies: My CXChat Summary on Artificial Intelligence, Machine Learning and the Customer

Business Over Broadway

According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT. Also, loyalty leaders infuse analytics into CX programs, including machine learning, data science and data integration.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. However, if we experiment with both parameters at the same time we will learn something about interactions between these system parameters.

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How Do Super Rookies Start Learning Data Analysis?

FineReport

If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you. Of course, other BI tools such as Power BI and Qlikview also have their own advantages. From Google.

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Bridging the Gap Between Analytics Expectations and Reality

Sisense

Some of those hurdles are overcome via dashboards, but they sit in a system several layers removed from anything that many people normally interact with. To achieve this, he says, companies should find ways to lower the cost of experimentation, decrease the time to value, and scale successful experimentation into products quickly.

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Themes and Conferences per Pacoid, Episode 6

Domino Data Lab

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Ensure a culture that supports a steady process of learning and experimentation. hill climbing ) ( Clue #1 ).