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Renette Youssef
  • Female
  • San Francisco, CA
  • United States
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Profile Information

Short Bio:
VP @ CrowdFlower. I am a self confessed gym junkie, coffee snob, foodie and world traveler. I've lived and worked in Sydney, London, Copenhagen and now sunny San Francisco.
Company:
CrowdFlower
Seniority:
VP
Industry:
Data Enrichment
LinkedIn Profile:
http://www.crowdflower.com
Interests:
Networking, Other

Renette Youssef's Blog

The Data Science Ecosystem in One Tidy Infographic

Posted on March 24, 2015 at 1:36pm 12 Comments

It probably comes as no surprise, but we talk to a lot of data scientists at CrowdFlower. We like learning the tools they use, the programs that make their lives easier, and how everything works together. Today, we'll really pleased to unveil the first of a three-part series about the data science ecosystem. Here it is in infographic form because, let's face it, everybody likes infographics: …

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CrowdFlower 's Open Source Data Library

Posted on March 9, 2015 at 9:00am 0 Comments

We think that open data is the new open source. We know data has become as important as software for many applications. And while there is lots of open-source software available, there are almost no good sources of open data. So CrowdFlower released large, high quality, real world data sets collected by our customers and published with their permission,…

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2015 Survey of Data Scientists Reveals Strategic Insights

Posted on February 10, 2015 at 8:30am 1 Comment

CrowdFlower Report Reveals: Data Scientists Say Messy Data and Lack of Time for Analysis Are Their Top Career Obstacles

2015 Survey of Data Scientists Uncovers What's Holding Them Back in Their Jobs and How Organizations Can Empower Them to Deliver Greater Strategic Value

CrowdFlower today released its 2015 Data Scientist Report. Findings revealed that data scientists saw messy, disorganized data as a major hurdle preventing them from doing what they find most…

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Guide: What is Human-in-the-Loop Machine Learning?

Posted on February 5, 2015 at 10:30am 0 Comments

Machine learning isn't a set-it-and-forget-it operation. Even with solid examples, ML algorithms can still fail and end up blocking important emails, filtering out useful content, and causing a variety of other problems.…

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