• ODSC West 2019 Warm-Up: Machine Learning

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    We want to invite you to participate in the ODSC Webinar! During it you will get to know more about four sessions you can attend at our conference in San Franciso on Oct 29th - Nov 1st, 2019. Date: July 24th, 2019 Time: 1:00 pm - 2:30 pm PST To access this webinar, please register using the link below: https://attendee.gotowebinar.com/register/4037580819899150349 Sessions: 1 - Causal Inference & Machine Learning Speaker: Vinod Bakthavachalam, Data Scientist at Coursera Lots of data science problems, especially towards informing business and product strategy, involve understanding causal relationships. The standard way to measure these is through AB testing, but many times that is infeasible, requiring alternative techniques from the causal inference that are an essential component of any data scientist's toolkit. The talk will walk through these techniques, some applications, and recent work at the intersection of causal inference and machine learning to handle large data sets. 2 - Real-ish Time Predictive Analytics with Spark Structured Streaming Speaker: Scott J Haines, Principal Software Engineer at Twilio In 20 short minutes learn what becomes possible when you add Spark into your analytics pipeline. Learn how to effectivley solve common Data Engineering problems with compile-time guarenttes - like how to ingest, normalize, transform and join datasets in realtime. Learn how to add insights on top of your streaming data with simple filters and pre-trained models. 3 - Visualizing Complexity: Dimensionality Reduction and Network Science Speaker: Jane Adams, Data Visualization Artist at University of Vermont Complex Systems Center Working with mathematicians, data scientists, and domain experts at the University of Vermont Complex Systems Center, data visualization artist Jane Adams has developed strategies for prototyping exploratory graphs of high-dimensional data. In this 90-minute workshop, Adams shares some of these methods for data discovery and interaction, navigating a creative workflow from paper prototypes of visual hypotheses through web-based interactive slices, offering critical insight for clustering, interpolation, and feature engineering. 4 - Healthcare NLP with a doctor's bag of notes Speaker: Andrew Long, PhD, Data Scientist at Fresenius Medical Care Nausea, vomiting, and diarrhea are words you would not frequently find in a natural language processing (NLP) project for tweets or product reviews. However, these words are common in healthcare. In fact, many clinical signs and patient symptoms (e.g. shortness of breath, fever, or chest pain) are only present in free-text notes and are not captured with structured numerical data. As a result, it is important for healthcare data scientists to be able to extract insight from unstructured clinical notes in electronic medical records. In this hands-on workshop, the audience will have the opportunity to complete a Python NLP project with doctors’ discharge summaries to predict unplanned hospital readmission. The audience will learn how to prepare data for a machine learning project, preprocess text using a bag-of-words approach, train a few predictive models, evaluate the performance of the models, and strategize how to improve the models. The MIMIC III data set is used in this tutorial and requires requesting access in advance (an artificial dataset will be provided for those without access).

  • ODSC WEST 2019

    Hyatt Regency San Francisco Airport

    Buy your ticket at: https://www.eventbrite.com/e/odsc-west-2019-open-data-science-conference-tickets-53970588483?discount=odsc70 About the Conference The annual ODSC West in San Francisco brings together the most influential data scientists, practitioners, innovators, and thought leaders in Data Science, Artificial Intelligence and Big Data. ODSC West showcases the best and the brightest when it comes to Data Science, including many open source data science pioneers. Learn from leading 210+ experts in hands-on trainings, workshops and talks on everything you need in applied data science and artificial intelligence. Day One - Accelerate AI and Training Sessions The Accelerate AI Business Summit holds talks and panels about the Business of AI and data science plus network with industry leaders. Day Two - Training Sessions Enhance your data science skills through training sessions taught by world-class data science instructors, in small class sizes. Here you'll strengthen your technical skills and boost your professional profile through hands-on trainings led by core contributors. Day's Three and Four - Workshop and Talk Sessions Further your data science knowledge and connect with like-minded individuals at the many conference talks and workshops. Tools, Topics, and Languages Impress your boss and colleagues with the skills you gain at ODSC West. Here’s just a sample of the tools, topics, and languages we'll be covering in 4 days: Topics: Recommendation Systems, Transfer Learning, Machine Vision, Autonomous Machines, Conversational AI, Data Science Research, Artificial Intelligence, Speech Recognition, Unsupervised Learning, Image Classification, Self-driving Vehicles, and Machine Translation Languages: Python, R Julia, Scala, Pig/Hive/NoSQL Tools: Python, Jupyter Notebooks, R programming, Julia, Scala, Stan, Apache Spark, MLlib, Streaming, Tensorflow, MXNet, Caffe, CNTK, Scikit-learn, Theano, Shogun, Pylearn2, Azure ML, Amazon ML,H20.ai, Cloud ML, Neo4J, D3.js, R-Shiny, Hadoop, Apache Storm, Apache Flink, Kafka, Druid Networking Opportunities Connect with 4,500 of your data science peers from around the world at these networking opportunities provided throughout the conference: Daily Coffee Breaks / Review the talks over coffee Career Expo / Cross paths with startups and Fortune 500 companies looking to hire talented data scientists Office Hours Session / Drop in and bring your questions, big and small Share a meal and ideas with like-minded individuals at Dinner with Data Scientists. (This a self-organized event. ODSC suggests the venue and provides a signup sheet. Each individual is responsible for their own dinner cost.)