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Data Science: Best and Worst Practices

" In this session, a data science leader will provide best practices for your data science project as well as tips to avoid landmines that could cause significant problems." This webcast was produced by Ted Fischer, specialist manager at Deloitte. #DataScienceCommunityDay

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Raise the Bar on Data Science ROI by Combining ML & Decision Optimization

"What if you could reduce your planning process from 1 week to 1 hour, or from 1 hour to 1 second? What if you could, at the click of a button, improve your bottom line by double digits? In this session, you will learn to do just that by leveraging IBM's powerful Machine Learning (ML) and...

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How to Get a Job in Data Science

" Data science is a massive field that encompasses hundreds of different titles and positions. Newcomers to the field get overwhelmed by the opaqueness of titles, the seemingly large list of requirements, a vast array of tools, and a large number of new trends that people feel they need to be...

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Extend SPSS Modeler Capabilities with Open Source

"Extend and embrace open source in SPSS Modeler, to programmatically perform tasks you can’t easily accomplish with out-of-the-box Modeler nodes. In this session, you will learn about the Python and R programming frameworks as implemented in SPSS Modeler V18.1. You will see examples of how...

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Automating Data Science Drudgery with Pixiedust

" The Jupyter notebook has quickly become one of data scientists’ favorite tools. When using them in IBM's Watson Studio, you get a complete platform for building an application - from data preparation and analytics to building and deploying machine learning models. Jupyter notebooks are a big...

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Data Science at Scale: Platform Decision

" Data science isn’t just creeping into areas of modern business, it’s being targeted in every department. Gone are the days where data science (DS) was a one-off project in hopes to improve a single area of the company. Organizations currently to take advantage of DS advancements in every...

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How to Fare Well in Machine Learning Competitions

" This session will introduce Kaggle machine learning competition platform, and describe an effective methodology to fare well on it, developed by a Kaggle Grand Master. The methodology covers data exploratory analysis, feature engineering, model evaluation, and algorithm tuning. Machine...

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Statistics for Data Science: What You Should Know and Why

"Data science is not only about machine learning. To be a successful data person, you also need a significant understanding of statistics. Gabriela de Queiroz walks you through the top five statistical concepts every Data Scientist should know to work with data." This webcast was produced by...

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Scalable Automatic Machine Learning with H2O

" In this presentation, Erin LeDell (Chief Machine Learning Scientist, H2O.ai), will provide an overview of the field of "Automatic Machine Learning" and introduce the new AutoML functionality in H2O. H2O's AutoML provides an easy-to-use interface which automates the process of training a large...

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The Social Economy of Open Source

"IBM is leading the industry in open source community engagement. Reflecting this external engagement into individual performance goals is challenging for both employees and managers. R provides an easy way to publish your code as a personal performance report with R markdown!" This webcast was...

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