• Sentiment Analysis: Deep Learning, Machine Learning, Lexicon Based? You choose!

    Do you want to know what your customers, users, contacts, or relatives really think? Find out by building your own sentiment analysis application. In this workshop you will build a sentiment analysis application, step by step, using KNIME Analytics Platform. After an introduction to the most common techniques used for sentiment analysis and text mining we will work in three groups, each one focusing on a different technique. Group 1 Deep Learning: This group will work with the visual Keras deep learning integration available in KNIME (completely code free) Group 2 Machine Learning: This group will use other machine learning techniques, based on native KNIME nodes Group 3 Lexicon Based: This group will focus on a lexicon based approach for sentiment analysis Agenda: 6:00pm – 6:20pm Registration and dinner 6:20pm – 6:40pm Introduction to KNIME Analytics Platform, with demo 6:40pm – 8:15pm Introduction to sentiment analysis and hands on workshop 8:15pm – Networking Workshop Requirements: Your own laptop preinstalled with KNIME Analytics Platform, which you can download from the KNIME website https://www.knime.com/downloads/download-knime KNIME Textprocessing extension. See video link, below about installing KNIME extensions. https://www.youtube.com/watch?v=8HMx3mjJXiw Help Installing KNIME Analytics Platform: Here are some links to YouTube videos to help you install KNIME Analytics Platform: Windows https://www.youtube.com/watch?v=yeHblDxakLk&feature=youtu.be Mac https://www.youtube.com/watch?v=1jvRWryJ220&feature=youtu.be Linux https://www.youtube.com/watch?v=wibggQYr4ZA&feature=youtu.be Extra Instructions for the Deep Learning Group: If you have already decided to work in the deep learning group, please pre-install Python and Keras. Just follow the instructions provided on our webpage about Deep Learning. https://www.knime.com/deeplearning/keras Additional Resource: If you would like to get familiar with KNIME Analytics Platform, you can explore the content of our E-learning course. https://www.knime.com/knime-introductory-course

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  • Data Science Learnathon: From Raw Data to Deployment

    Microsoft Technology Center

    This Learnathon is part of our US KNIME Data Science Roadshow, where the KNIME-obile is travelling from coast to coast - from Boston to San Francisco, making stops in New York, Denver, and many other cities - where we will meet together to learn and build workflows. On March 22, the KNIME-obile is in New York! Note: This is a free event and open to everybody who is interested. So, what is a Learnathon? A learnathon is in between a hackathon and a workshop. It’s like a workshop because we’ll learn more about the data science cycle - data access, data blending, data preparation, model training, optimization, testing, and deployment. It’s like a hackathon because we’ll work in groups to hack a workflow-based solution to guided exercises. The tool of choice for this Learnathon is the open-source, GUI-driven KNIME Analytics Platform. Because KNIME is open, it offers great integrations with an IDE environment for R, Python; SQL, and Spark. After an initial introduction to the tool and to the data science cycle, we will split in groups. Each group will focus on one of three aspects of the data science cycle: Group 1: Working on the raw data. Data access and data preparation Group 2: Machine Learning. Which model shall I use? Which parameters? Group 3: I have a great model, now what? The model deployment phase. We will provide a few datasets, jump-start workflows and final solutions for the proposed tasks, and of course data science experts. Please bring your own laptop with KNIME Analytics Platform pre-installed. To install KNIME Analytics Platform, follow the instructions provided in these YouTube videos: Windows (https://www.youtube.com/watch?v=yeHblDxakLk&feature=youtu.be) Mac (https://www.youtube.com/watch?v=1jvRWryJ220&feature=youtu.be) Linux (https://www.youtube.com/watch?v=wibggQYr4ZA&feature=youtu.be) If you would like to get familiar with KNIME Analytics Platform, you can explore the content of our E-learning course (https://www.knime.com/knime-introductory-course). Please also download the workshop material (jump-start workflows and instructions) from here (https://www.dropbox.com/s/f9wqpyfxjxvlgo0/Learnathon_2018.knar?dl=0). We will import this material during the Learnathon. Here's a more detailed agenda of the event. 17:30 – 18:00 : Networking and dinner 18:00 – 18:20 : Introduction to KNIME Analytics Platform 18:20 – 18:40 : The Data Science cycle: from raw data to deployment 18:40 – 19:00 : Data sets and tasks presentation; group formation 19:00 – 21:00 : Let’s work & learn! Are you ready to learn? Sign up now! We are looking forward to seeing you!

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  • Tableau/KNIME Joint User Group Meeting

    Consumer Reports

    DESCRIPTION Consumer Reports has generously offered meeting space for our next Westchester Tableau User Group (TUG) meeting. The event will be on Tuesday, September 26th, from 8:30 AM to 11:00 AM. WEBEX INFORMATION: https://crevents.webex.com/crevents/j.php?MTID=m8a2b41e64c55fc682b2c14f5e55afdce WebEx Password: Only WebEx Mobile app users are required to enter a password: BYR2x6Bg If you are prompted for a password when using the URL, try refreshing your browser. We expect everything to run smoothly. In the event, we run into any technical issues we will send out an email with additional instructions. Please let me know if you have any questions or suggestions. Agenda 8:30 to 9:00 -- Coffee & Pastries 9:00 to 9:05 ‐- Welcome from Michelle Leonard, Consumer Reports, and Steve Wexler, Data Revelations 9:05 to 9:55 -- Everything Before the Dashboard – Tools of Data Prep 9:55 to 10:05 -- Killer Tips and Techniques 10:05 to 10:20 -- Networking and Break 10:20 to 11:00 -- Easy-Breezy Data Prep in KNIME Everything Before the Dashboard – Tools of Data Prep Working with Tableau is a breeze...as long as your data is clean and ready to go. Unfortunately, you may not always have the time, expertise, or resources for a full service, enterprise ETL solution. There are, however, a litany of tools to help us coerce our not-so-cooperative datasets into useable formats for Tableau. Sometimes called 'Swiss Army Knives' of data prep, we'll take a look at a few of these tools, including Dataiku and Keboola, and a live demo of Alteryx, to show how Tableau users can leverage these tools quickly and easily. Bio: Jimmy Steinmetz is an Analytics Consultant with InterWorks, Tableau's first Gold Partner. With experience across many verticals and clients ranging in size from global organizations to mom-and-pop shops, he's well versed in bad data (and how to work with it!). He has worked on projects to develop and promote agile, useful, and sustainable data analytics and visualization solutions. Despite having spent most of his life in Indiana and spending much of his time on the road, he now calls the East Village of Manhattan home. Killer Tips and Techniques -- Volume 1 Expect to learn two to four killer tips/techniques in five to ten minutes. These are easy-to-digest morsels that you can immediately apply to your own work. Bio: Steve Wexler is the founder of Data Revelations and co-author of The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios (Wiley, 2017). Steve has worked with ADP, Gallup, Deloitte, Convergys, Consumer Reports, The Economist, ConEd, D&B, Marist, Cornell University, Stanford University, Tradeweb, Tiffany, McKinsey & Company, and many other organizations to help them understand and visualize their data. Steve is a Tableau Zen Master, Iron Viz Champion, and Tableau Training Partner. Easy-Breezy Data Prep in KNIME We all know that Customer Segmentation is a routinely applied to better understand our customer segments, in terms of revenue creation, loyalty, demographics, buying behavior, or any combination of these criteria and more. There are many flavors of customer segmentation, but the basic concept is easy: group together customers based on similarity in a given area. Customer Segmentation is also very easy to implement on KNIME Analytics Platform, given the intuitive and easy to learn Graphical User Interface. KNIME Analytics Platform is also open source and downloadable for free from www.knime.org (http://www.knime.org/). At the end of the analysis, Customer Segments must be visualized for better understanding and Tableau is a great tool for visualization. In this second talk, we combined the ease of use of KNIME for data blending and machine learning and the visualization strength of Tableau, to get an elegant customer segmentation solution in very short time. Short Bio Bio: Vincenzo Tursi has been a data scientist at KNIME for the past year and half. During this time he has worked on text processing, network graph analysis, and 360 degrees customer data analytics. He is currently writing a book on text processing using KNIME. Before joining KNIME, Vincenzo worked as Business Consultant for Capgemini S.p.A and Business Integration Partners S.p.A. in Italy. He then moved to Germany for a short time period as Research Associate at Saarland University.

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  • KNIME Introduction & Use Cases

    WebEx Link: https://crevents.webex.com/crevents/j.php?MTID=m03a39c3a6e6360bb196acb4390779591

    Date: July 20th Time: 7 PM - 8:15 PM EST Location: WebEx (RSVP and you'll receive an email with login details) Presentations: Introduction to KNIME by Dr. Doris Sullivan, Consumer Reports Dr. Doris Sullivan is the Associate Director for Product Safety in Consumer Reports’ Consumer Safety and Sustainability Group. She oversees product safety testing, research, and prioritization. She is also an expert in compiling and analyzing large datasets. She received her Ph.D. in computational chemistry from Boston University and completed postdoctoral research at the Free University of Brussels and University of Pennsylvania. Review of data science use cases: from classic to more innovative by Rosaria Silipo, Principal Data Scientist, KNIME Dr. Rosaria Silipo is not only an expert in data mining, machine learning, reporting, and data warehousing, she has become a recognized expert on the KNIME data mining engine, about which she has published three books: KNIME Beginner’s Luck, The KNIME Cookbook, and The KNIME Booklet for SAS Users. Previously Dr. Silipo worked as a freelance data analyst for many companies throughout Europe. She has also led the SAS development group at Viseca (Zürich), implemented the speech-to-text and text-to-speech interfaces in C# at Spoken Translation (Berkeley, California), and developed a number of speech recognition engines in different languages at Nuance Communications (Menlo Park, California). Dr. Silipo gained her doctorate in biomedical engineering in 1996 from the University of Florence, Italy.

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