- DSS-2019-05: CHLOE WARNER and AMAN ARORA
Data Science Sydney proudly presents our speakers for May 2019: CHLOE WARNER: "Deep Learning feat. Charles Darwin: using evolutionary insights to explore your data" AMAN ARORA: “Demystifying Transfer Learning - what's exactly going on and why is it so popular?” 200 seats available, first come - first served for members on the RSVP-yes list. Please ensure that you keep your RSVP up to date. If you cannot make it, please make you spot available for others as soon as possible. Subscribe to our YouTube channel: https://www.youtube.com/channel/UCMNZrokQNSm2UQ_T5VfOLgg To comply with CBA Security we need your FIRST and LAST NAME before the event. If these are not your profile name, please enter them when you register. Members who do not provide first and last name will be removed from the guest list and will not be able to attend. Registration opens at 5:30pm and close at 6:15pm, sharp. Food and beverages between 6pm and 6:15pm and late comers cannot be admitted. --- CHLOE WARNER: "Deep Learning feat. Charles Darwin: using evolutionary insights to explore your data" About the Talk: Neural networks are the “black boxes” of the data science world. We can be amazed by their ability to solve complex problems. At other times, they struggle to solve seemingly simple problems and can seem frustratingly stupid. We’ll talk about the application of a neural network to a seemingly simple timeseries pattern recognition problem and leveraging the “dark art” of hyperparameter tuning to explore the patterns in your data. About the speaker: Chloe is a prognostics engineer at Komatsu Mining Corp. where she uses established and up-and-coming modelling methods to turn machine sensor data into happy customers. With a background in mechatronics engineering, she completed an honours thesis in the use of deep learning and genetic algorithms for pattern recognition. ----- AMAN ARORA: “Demystifying Transfer Learning - what's exactly going on and why is it so popular?” About the talk: Transfer Learning is perhaps the reason why deep learning is so successful and is able to achieve great results across various domains. In the words of an expert data scientist and fast.ai founder Jeremy Howard 'Every time we put transfer learning into anything, we generally make it much better'. In mid-2018 Jeremy Howard and Sebastian Ruder put transfer learning to test in NLP and the proposed method(ULMFiT) significantly outperformed existing state-of-art on six text classification tasks reducing the error by 18-24% on the majority of datasets. Through this talk let's demystify transfer learning and understand what's really going on under the hood and why is this method so successful. About the speaker: Aman works as a data scientist at CoreLogic Australia in the Automated Valuations team where he works on perfecting prediction algorithms to predict property prices. He has previously worked on projects across various verticals such as image recognition, text analysis, recommendation systems, demand forecasting and has a deep passion for Deep Learning. In his free time he loves to fire up a GPU instance and try out new ideas on Kaggle competitions and look for innovative ways to provide value to the business.
- Data Showdown 2019
Must Register Here: https://www.eventbrite.com.au/e/data-showdown-2019-tickets-56393984927 Judges * Dr. Eugene Dubossarsky, Director, Principal Trainer, Presciient * Mitra Heravizadeh, Head of Strategy & Architecture, AMP * Kieran Clulow, Data Engineering Director, IAG * TBC * TBC Format * 7 Teams of 2-3 people, presenting their data solution to an audience of 800 people. * 7 min per presentation + questions * Panel of judges, scoring each presentation * At the end of the evening Australia's best data team announced! Do you want to share your data solution at the event? Any teams looking to present a data solution at the event please email [masked] with your presentation and solution summary, along with the benefit it will provide to the audience, by the 19th of April 2019. If you'd like to discuss in further detail you can also call Gerhard on[masked]. Rules for Presentation / Judging Criteria * No Vendor Pitches * Present a Data Solution which your team have worked on, stating its use case or the business problem it solves. * Potential topic areas: Big Data, data integration, analytics, ML, AI * Contestants will be judged on the value that their contribution delivers. It is therefore important that they spell out the relevant KPIs, and compare with benchmarks where appropriate. * Contestants will be judged on KPI performance, but also on the appropriateness of the KPI, and the context of measurement (such as benchmarks). * Where sophisticated technology such as AI / Machine Learning are used, contestants are encouraged to explain the need for the sophistication, and the advantage over simpler techniques. * Contestants will be judged on APPROPRIATE sophistication. * Finally, contestants will be judged on how engaging they are in their presentation style. Call for sponsors * If you'd like to sponsor the Data Showdown please reach out to [masked] or call Stephen on[masked] * ROI: Full list of registrations for marketing purposes, Banners on Stage, 1 minute stage time to pitch to the audience, logo digital banner and event pages. This is a sponsor funded event your registration details will be shared with sponsors for marketing purposes. Also please read our code of conduct: https://meetupmadness.io/code-of-conduct/