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Cloudera Machine Learning

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  • Driving Value with Data Science
    Driving Value with Data Science
    Thomas W. Dinsmore, Director of Product Marketing, Cloudera Data Science Recorded: Dec 12 2017 46 mins
    This is the age of data science. We have more data, computing power and software packages than ever before, and we’re driving real value with data science. But challenges remain: fragmented and dirty data, collaboration issues, and long project cycle times.

    Keys to success: a ‘data-first’ approach, enabling collaboration, and a focus on prediction. Cloudera Data Science delivers the unified platform you need for rapid time to value with the most advanced machine learning techniques, including deep learning.
  • Introducing the Cloudera Data Science Workbench
    Introducing the Cloudera Data Science Workbench
    Matt Brandwein, Tristen Zajonc Recorded: Nov 15 2017 47 mins
    Let's talk about the emergence of open source tools for data science, common gaps in the data science ecosystem, and introduce a new tool from Cloudera with a demonstration.
  • How to: Deep Learning with Cloudera
    How to: Deep Learning with Cloudera
    Thomas Dinsmore Recorded: Nov 15 2017 63 mins
    Deep learning expands boundaries of the possible. Detecting fraud. Predicting claims. Diagnosing cancer. Deep learning solves these problems and many others. However, organizations struggle to make deep learning work. Cloudera—with tools like the Cloudera Data Science Workbench—helps you bring deep learning to your data, for new insights and applications. A demonstration of Cloudera Data Science Workbench is included in the webinar.
    3 things to learn: Practical ways to move forward with deep learning, deep learning without massive new investments, and how to implement self-service deep learning on demand.
  • Wargaming.net: Analyzing 550 Million Daily Events to Increase Customer Lifetime
    Wargaming.net: Analyzing 550 Million Daily Events to Increase Customer Lifetime
    Sergei Vasiuk Recorded: Oct 5 2017 4 mins
    Wargaming has implemented a “state of the art” enterprise data platform that can be scaled to store massive amounts of game data and produce relevant management KPIs and interface for data analytics.

    Overall, the Wargaming team has to process over 3TB of raw data daily. Cloudera Enterprise is the cornerstone for this purpose and the data reservoir is where data teams store all the raw data. Wargaming then uses machine learning techniques to better understand the players, their needs, and if the game provided an enjoyable experience.
  • Demo: Cloudera Data Science Workbench
    Demo: Cloudera Data Science Workbench
    Sean Anderson Recorded: Jul 11 2017 8 mins
    Machine learning is all about the data, but it's often out of reach for analytics teams working at scale. Cloudera Data Science Workbench enables fast, easy, and secure self-service data science for the enterprise.

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