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      Enterprise Data Science Architecture Conference in Melbourne


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      March 27, 2020

       

      Melbourne, Victoria, Australia
      Melbourne, Victoria

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      EVENT DETAILS
      Enterprise Data Science Architecture Conference

      The Enterprise Data Science Architecture Conference focuses on how to properly productionise data science solutions at scale. We have confirmed speakers from ANZ Bank, Coles Group, SEEK, Microsoft, AWS and Growing Data. The combination of presentations is intended to paint a complete picture of what it takes to productionise a profitable data science solution.

      Our field flies fast. Keep your skills current.
      As an industry, we are figuring out how to best build end-to-end machine learning solutions. The workflow starts with data sourcing, data preparation, feature engineering, building the machine learning model, testing the ML model, deploying to production, monitoring in production, getting feedback and then repeating the process with improved models and better features. Companies are currently learning how to build it all into one smooth pipeline. The presentations at our conference will show you what works today in leading enterprises. Reserve your place now at https://edsaconf.io, while early bird tickets are still available.

      Your toolkit for real projects.
      Enterprise scale brings its own challenges and solutions. Automation, resilience, scalability and the appropriateness of the data science techniques used have significant impact on profit and loss. Governance is also important because of privacy laws and because large enterprises often operate in regulated industries. The presentations at our conference will focus on how enterprises are productionising machine learning solutions. We are still learning as an industry. Knowledge of best practices in end-to-end machine learning pipelines will become essential skills - demanded by clients and employers. Keep your skills current. Register today at https://edsaconf.io

      Real Solutions, Done Properly
      Learn from leaders who deploy real data science solutions in their organisations. Our projects have many names: data science, machine learning (ML), artificial intelligence (AI), analytics and other impressive terms. What matters are the results. Increasing profit, saving lives, managing risk, automating manual labour. The presentations at our conference will show you how enterprises are doing it right.

      Our industry moves fast. Don't get left behind. Buy your ticket to learn best practices and keep up with the latest innovations.

      Our presentations will focus on how to properly deploy data science solutions in the enterprise.

      The conference will be held 27th March 2020 at the Melbourne Marriott Hotel. Conference delegates will enjoy morning tea, lunch, afternoon tea and evening drinks/canapes. Reserve your place at https://edsaconf.io Early bird tickets are limited in quantity and are on sale until next month - reserve an early bird ticket for best value.

      Recent Gartner and Capgemini studies predict only around 25% of AI/data science projects are successful and only around 15% make it to full-scale production. Of these, many degrade in performance and produce disappointing results within months of implementation. Presentations at our conference will include real working solutions that are currently producing good results. Buy your ticket https://edsaconf.io to learn how it's done properly.

      Cost: Payment required - Early Bird - AUD $880 Buy early bird tickets now. Limited quantity available. On sale until 24/11/2019. Early Bird Stage Two - AUD $891 This second chance will fly fast. Limited quantity available. On sale until 30/11/2019. General Admission - AUD $990 General Admission Ticket for the Enterprise Data Science Architecture Conference. On sale until 15/03/2020.

      Categories: Conferences & Tradeshows | Science | Technology

      Event details may change at any time, always check with the event organizer when planning to attend this event or purchase tickets.

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