• Deep Learning Sydney: TensorFlow 2.0

    AWS Sydney

    Thanks to Iman Eftekhari (Intellify) and Koorosh Lohrasbi (AWS) for sponsoring our great Deep Learning Sydney meetup in May! Agenda for 28th/May/2019 Location: AWS on Level 37, 2 Park St, Sydney, NSW 2000 5:45pm: Catering Enjoy Pizza and Drinks. 6:26pm: Opening speech, and housekeeping words by Richard Xu and Andy Zeng 6:30pm: Talk by Kale Temple from Intellify Abstract: Time-series, as a field of study, has largely focused on statistical methods that work well under strict assumptions. Specifically, when there is sufficient history, there is little meta-data and a well-formed auto-correlation structure. However, as an applied practitioner I know that most real-world time series problems violate these assumptions. This leaves us with an opportunity to use more modern time series methods, based on machine learning (and deep learning), to overcome these deficiencies. This session is designed to briefly speak about the unique properties of time-series, how statistical methods work and how and why machine learning (and deep learning) methods can be used to improve accuracy. Speaker intro: Kale Temple is the Co-founder and Practice Director at Intellify, a Data science and machine learning consultancy. He has been working in analytics and data science consulting for 5+ years and has helped a number of the world’s leading corporate and government organisations to deliver high impact data projects. He is currently an Honorary Affiliate of the University of Sydney’s Business School. 6:50pm: What is NEW in TensorFlow 2.0 by Erica Huang Abstract: In this talk, Erica will show audience a series of demos using TensorFlow 2.0; In here, she has included several examples to highlight the new features of TensorFlow 2.0 and to compare and contrast with that of TensorFlow 1.0 Speaker intro: Ms Erica Huang graduated from Honors (first class) from University of Sydney in 2016. She is currently a PhD student at University of Technology Sydney (UTS) supervised by Prof Richard Xu. She is specializing in probabilistic Deep Learning Generation. 7:10pm: What is new in Deep Learning by Andy Zeng This is Andy’s usual section on showing audience all the goodies happening in Deep Learning in the last six months. 7:20pm Announcements and closing remarks by Iman Eftekhari and Koorosh Lohrasbi 7:30pm – 8:30 Social time We encourage people to stay and to socialize. We strive to make the meetup a real “meetup” event. So please stay and enjoy the night with hundreds of Deep Learners!

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  • Deep Learning Sydney September meetup @ AWS

    AWS Sydney

    6:00pm: Catering Enjoy Pizza and Drinks. 6:30pm: Opening speech, and housekeeping words by Andy Zeng and Ben Thurgood 6:40pm: Talk by Ian Oppermann Abstract: TBA Speaker intro: Dr. Ian Oppermann is the NSW Government’s Chief Data Scientist and CEO of the NSW Data Analytics Centre. Ian has 25 years’ experience in the ICT sector and, has led organizations with more than 300 people, delivering products and outcomes that have impacted hundreds of millions of people globally. He has held senior management roles in Europe and Australia as Director for Radio Access Performance at Nokia, Global Head of Sales Partnering (network software) at Nokia Siemens Networks, and then Divisional Chief and Flagship Director at CSIRO. 7:05pm: Deep NLP TensorFlow tutorials by Erica Huang Abstract: In this tutorial, Erica will show audience systematically of how to code a series of Deep NLP demo using TensorFlow; in this tutorial, she has included examples on text classification using both LSTM and CNN, as well as using Seq2Seq for language translations. Speaker intro: Ms Erica Huang graduated from Honors (first class) from University of Sydney in 2016. She is currently a PhD student at University of Technology Sydney working on natural language processing research; she specializes in natural language to image generation. 7:30pm: What is new in Deep Learning by Andy Zeng This is Andy’s usual section on showing audience all the goodies happening in Deep Learning in the last few months. 7:40pm Announcements and closing remarks by Andy Zeng and Ben Thurgood 7:50pm – 8:30 Social time We encourage people to stay and to socialize. We strive to make the meetup a real “meetup” event. So please stay and enjoy the night with hundreds of Deep Learners!

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  • NVIDIA AI Conference Sydney 3-4 September

    Sydney Convention and Exhibition Centre - ICC Sydney

    Please do not RSVP via Meetup, instead, please register via the link below: https://www.nvidia.com/en-au/ai-conference/ This is the conference description given by NVIDIA (and see the discount code supplied by NVIDIA): "Join us at the premier AI and deep learning event in Australia: NVIDIA’s AI Conference 2018. NVIDIA AI Conference takes place September 3-4, 2018 in ICC Sydney. The conference showcases the latest breakthroughs from major enterprises, rising AI startups and universities in a wide range of fields such as deep learning for commercial enterprise, robotics, intelligent video analytics, virtual reality and more. You’ll hear from technology leaders and disruptive startups, along with NVIDIA researchers, engineers, and executives. NVIDIA AI Conference offers substantial networking opportunities, exhibits, and an evening reception. The agenda also includes hands-on, classroom-style workshops led by industry experts from the NVIDIA Deep Learning Institute. To register, use the following code NVAIDLS to get a special rate of $75 for the conference (save 50% off regular rates), and $350 for the conference and workshops (30% off regular rates)."

  • Deep Learning Sydney August meetup @ QBE

    2 park street

    Dear Sydney Deep Learners, Location: QBE on Level 5, 2 Park St, Sydney, NSW 2000 Sponsor: QBE 6:00pm: Catering Enjoy Pizza and Drinks. 6:30pm: Opening speech by Richard Xu and Andy Zeng 6:35pm: Some housekeeping words from our host QBE Insurance 6:40pm: “Operationalizing Deep learning models in QBE: The journey from models to business outcomes” by Dr Mark De Deuge Abstract: This talk will cover the journey of the QBE data science team in deploying language agnostic machine learning solutions. We will focus on a use case that leverages deep learning to suggest changes to potentially miss represented claims and the architectures we use to deploy and scale this solution. Speaker intro: Dr Mark De Deuge is the Principal Data Scientist at QBE Insurance, where he focuses on a range of problems, from structuring analytics frameworks and tooling to development of the data science capability at QBE and delivery of solutions to real-world problems by combining machine learning and software engineering. Prior to QBE he worked on the customer engagement platform at CBA where he developed the algorithmic approaches to ranking marketing and engagement conversations for millions of customers. He has a PhD in machine learning from USYD where he focused on generating simple deep learning architectures for ground robotics, trading off performance for computational cost. 7:05pm: "When Deep Learning Meets e-Commerce (probably part 2) "by Andy Zeng Abstract: Half year ago, when Andy announced that he was joining an e-commerce company, a few friends asked him – “do you think you can apply deep learning in e-commerce”? He said, “I’ll see”. Half year later, he brought the answer back, and to talk about it seriously: “How is deep learning been utilized in e-Commerce?” Speaker intro: Dr. Andy Zeng is the co-founder of Deep Learning Sydney. He is now the Director of Data Science at JollyChic, a fast growing B2C e-Commerce platform world-widely. He is also an adjunct associate at UTS. He has 10+ years’ experience in data science. His experience varies from academic research to industry engagements, from data science consulting to in-house data science capability development, from hands on project delivery to data science team management. 7:15pm: Mid Break 7:30pm: Special talk from Dr Laurens van der Maaten Live from Face AI Research (New York) Title: Exploring the Limits of Convolutional Networks Abstract: This talk presents two of our recent studies on models for image classification. First, I will present our work on novel convolutional-network architectures, in particular, an architecture called multi-scale DenseNets that allows for trading off model accuracy and computational costs dynamically at test time. This improves the average accuracy of the model given a computational budget and it facilitates better load balancing of image-classification web services. Second, I will present our work on developing models that are pre-trained on billions of web images without manual annotation. These models achieve a state-of-the-art accuracy on ImageNet of 85.4% top-1 error (single crop), an improvement of more than 2% over the prior state-of-the-art. This talk describes joint work with Gao Huang, Zhuang Liu, and Kilian Weinberger (Cornell University) and Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, and Ashwin Bharambe (Facebook). Speaker intro: He is Research Scientist at Facebook AI Research in New York, working on machine learning and computer vision. Before, he worked as an Assistant Professor at Delft University of Technology, as a post-doctoral researcher at UC San Diego, and as a Ph.D. student at Tilburg University. He interested in a variety of topics in machine learning and computer vision. Currently, he is working on embedding models, large-scale weakly supervised learning, visual reasoning, and cost-sensitive learning. 8:00pm-8:30pm: Social Session

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  • Deep Learning Sydney July meetup @ Google

    Google offices @ Fairfax

    Dear Sydney Deep Learners, This is what we all have been waiting for: July's Deep Learning Sydney (DLS) meetup is coming: 30th/July! We'd like to give our sincere thanks to our sponsor Google for supporting us with venue, pizza and drinks (non-alcohol) - in particular, a special thanks to Brett Morgan and Ankur Kotwal from Google! Agenda of 2018 July Deep Learning Sydney Meet-up http://www.meetup.com/Deep-Learning-Sydney/ 30th/July/2018 Location: One Darling Island Rd, Pyrmont NSW 2009 Sponsor: Google 6:00pm: Catering Enjoy Pizza and Drinks. 6:30pm: Opening speech by Richard Xu and Andy Zeng (Andy will dial in remotely) 6:35pm: Some housekeeping words from our host Google 6:40pm: A talk + Deep Learning demo from Google by Ankur Kotwal Abstract: TBA Speaker intro: TBA 7:05pm: "When Probability models meet with Neural Networks" by Richard Xu Abstract: Deep Learning is currently dominating the machine-learning realm, and will be so for the near future. However, probabilistic methods, especially the Bayesian methodologies are still useful in many areas. Interestingly, many deep learning mythologies can be found to have close resemblance with their Bayesian counterparts, for example, those between Recurrent Neural Networks and Recursive Bayesian Estimation. Many probability methods have also assisted the deep learning methodologies such as the classic Expectation Maximization has been found to assist recently popular matrix capsule’s routing algorithm, as well as how Gumbel-Max trick has been helping to re-parametrize softmax distributions. In this talk, we will go through some of the popular probabilistic models and to make some very interesting relationships with many recently popular Deep Learning methodologies Speaker Intro: A/Prof Richard Xu is an associate professor in machine learning at UTS whom manages a team of 30 academics, postdocs, PhD students, engineers and communicators to apply their minds and talents to an array of theoretical research as well as industry projects for a growing list of multinational and Australian businesses and government agencies; He also publish 1000+ slides of Statistics, Probability and Machine Learning (including Deep Learning) courses for PhD students and ML practitioners around the world. In addition, he also developed the most popular Mandarin-speaking Machine Learning video course. He is the co-founder of Deep Learning Sydney. 7:15pm: "When Deep Learning Meets e-Commerce (probably part 1) "by Andy Zeng abstract: Half year ago, when Andy announced that he was joining an e-commerce company, a few friends asked him – “do you think you can apply deep learning in e-commerce”? He said, “I’ll see”. Half year later, he brought the answer back, and to talk about it seriously: “How is deep learning been utilized in e-Commerce?” If he cannot finish within 10 mins. He is going to make it a part one. Speaker intro: Dr. Andy Zeng is the co-founder of Deep Learning Sydney. He is now the Director of Data Science at JollyChic, a fast growing B2C e-Commerce platform world-widely (ranking No. 1 in mid-east region). He is also an adjunct associate at UTS. He's got 10+ years’ experience in data science. His experience varies from academic research to industry engagements, from data science consulting to in-house data science capability development, from hands on project delivery to data science team management. 7:30pm: Announcement This is an announcement session for anyone to announce anything relates to deep learning and data science (e.g., hiring, new meetup, new startup). 7:40pm-8:30pm: Social Session We encourage people to stay and to socialize. We strive to make the meetup a real “meetup” event. In this session, we will serve drinks (alcohol and non-alcohol) and finger food till 8:30pm. So please stay and enjoy the night with hundreds of Deep Learners!

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  • Our great First Deep Learning Sydney meetup in 2018!

    Agenda of 2018 Feb Deep Learning Sydney Meet-up http://www.meetup.com/Deep-Learning-Sydney/ 26th/Feb/2018 Location: Level 37, 2 Park St Sponsor: AWS Sydney 6:00pm: Catering Enjoy Pizza and Beers. 6:30pm: Opening speech by Andy Zeng and Richard Xu Andy (dial in remotely) and Richard will open the brand new 2018 meetup 6:40pm: MATLAB for Deep Learning by David Willingham Abstract: In this talk, David will show a demo on how to: • Develop end to end systems that rely on Deep Learning (such as Autonomous Vehicles) • Automate ground-truth labelling using apps. • Work with existing models from Caffe and TensorFlow-Keras. • Accelerate training using multiple GPUs, the cloud, or clusters. • Visualize intermediate results, tune and debug deep learning models. • Deploy the model anywhere: On the cloud, desktop or even a mobile GPU • Run the deployed model fast Speaker intro: David is a Data Analytics Engineer, specializing in using data science to find value in both Business & Engineering Data. Focusing in core areas of Data Analytics, Deep Learning, Big Data, Internet of Things, Predictive Modelling & Data Mining. Over 10 years’ full time experience developing in professional data analytics software: 1. Providing guidance and developing technical solutions in the area of data analytics 2. Analyzing users' problems to determine and implement the best computational approach. 6:55pm: "PTZ-Static camera system 12 years later: into the Deep Learning Era", by UTS Deep Learning research tem (remotely) Abstract: Compare what we did 12 years ago: https://www.youtube.com/watch?v=MURT6pZ4p7E We have now revolutionized the system by using Deep Learning! It delivers robustness and real-time performance! And a lot of exciting research to be unleashed! 7:05pm: "How to Train a Neural Network faster: Batch and Layer Normalization" by Richard Xu Abstract: DLS cannot be without some Deep Learning Theories: In this talk, Richard will give a 15 minutes’ gentle introduction into the theories and practice of how Batch and Layer Normalization work in Deep Learning: The source code for the demo is written in Python, and can be downloaded from github: https://github.com/roboticcam/matlab2python/blob/master/batch_norm.ipynb Speaker Intro: A/Prof Richard Xu is an associate professor in machine learning at UTS whom manages a team of 30 academics, postdocs, PhD students, engineers and communicators to apply their minds and talents to an array of theoretical research as well as industry projects for a growing list of multinational and Australian businesses and government agencies; He also publish more than 800 slides of Statistics, Probability and Machine Learning (including Deep Learning) courses for PhD students and ML practitioners around the world. In addition, he also developed the most popular Mandarin-speaking Machine Learning video course. He is the co-founder of Deep Learning Sydney. 7:20pm: "What’s new in Deep Learning" by Andy Zeng abstract: All the latest goodies in Deep Learning. Speaker intro: Dr. Andy Zeng is the co-founder of Deep Learning Sydney. He is now the Director of Data Science at JollyChic, a fast growing B2C e-Commerce platform world-widely (ranking No. 1 in mid-east region). He is also an adjunct associate at UTS. He's got 10+ years’ experience in data science. His experience varies from academic research to industry engagements, from data science consulting to in-house data science capability development, from hands on project delivery to data science team management. 7:30pm: Announcement This is an announcement session for anyone to announce anything relates to deep learning and data science (e.g., hiring, new meetup, new startup). 7:40pm-8:30pm: Social Session We encourage people to stay and to socialize. We strive to make the meetup a real “meetup” event. In this session, we will serve drinks (alcohol and non-alcohol) and finger food till 8:30pm.

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  • Deep Learning Sydney August meetup

    AWS Sydney

    This is what we all have been waiting for: August's Deep Learning Sydney (DLS) meetup! We'd like to give our sincere thanks to our sponsor Amazon Web Services. In this meetup event, we have invited Dr. Maximilian Nickel, Research Scientist from Facebook to give us an exciting talk. There are potentially 1-2 additional internationally-renowned Deep Learning researchers speaking at this meetup which will be announced soon. The agenda of the event is as follows: Location: Level 37, 2 Park St. Sydney (note that ASW checks attendees against RSVP list and so please also bring your IDs too. Please note that, you need to be RSVPed in order to attend this one) 6:00pm: Catering Enjoy Food and beverages. 6:25pm: Opening 6:30pm – 6:50pm: “Poincaré Embeddings for Learning Hierarchical Representations”, by Maximilian Nickel, Research Fellow @ Facebook Speaker intro: Maximilian Nickel is a research scientist at Facebook AI Research in New York. Before joining FAIR, he was a postdoctoral fellow at MIT where he was with the Laboratory for Computational and Statistical Learning and the Center for Brains, Minds and Machines. In 2013, he received his PhD with summa cum laude from the Ludwig Maximilian University Munich. From 2010 to 2013 he worked as a research assistant at Siemens Corporate Technology. His research centers around embedding methods for learning and reasoning with relational knowledge representations and their applications in artificial intelligence, machine reading, and question answering. Abstract: Representation learning has become an invaluable approach for learning from symbolic data such as text and graphs. However, while complex symbolic datasets often exhibit a latent hierarchical structure, state-of-the-art methods typically do not account for this property. For this purpose, we introduce a new approach for learning hierarchical representations of symbolic data by embedding them into hyperbolic space -- or more precisely into an n-dimensional Poincaré ball. Due to the underlying hyperbolic geometry, this allows us to learn parsimonious representations of symbolic data that simultaneously capture hierarchy and similarity. We introduce an efficient algorithm to learn the embeddings based on Riemannian optimization and show experimentally that Poincaré embeddings outperform Euclidean embeddings significantly on data with latent hierarchies, both in terms of representation capacity and in terms of generalization ability. 6:50pm-7:20pm: Place holder for other potential speakers 7:20pm – 7:30pm: Announcement This is an announcement session. Anyone who would announce anything relates to deep learning and data science (e.g., hiring, new meetup, and new startup), please contact Andy for proper arrangement. 7:30pm – 8:00pm: Social Session We encourage people to stay and to socialize. We strive to make the meetup a real “meetup” event. So please stay and enjoy the night with hundreds of Deep Learners!

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  • May's Deep Learning Sydney Meet-up: Exciting, Fun and Informative!

    Sydney Mechanical School of Arts

    Dear guys, This is what we all have been waiting for: May's Deep Learning Sydney (DLS) meetup is around the corner! We'd like to thank our sponsor Servian Pty Ltd! As always, it's a fun, exciting and informative event with talks and demos; More importantly, it's an event where Deep Learners in Sydney get to meet each other. So come and join us! The agenda of the night are as follows: Second Deep Learning Sydney Meet-up http://www.meetup.com/Deep-Learning-Sydney/ 15th/May/2017 6:00pm Location: Sydney Mechanical School of Arts (https://maps.google.com/maps?f=q&hl=en&q=280+Pitt+St%2C+Sydney+NSW+2000%2C+Sydney%2C+au) 280 Pitt St, Sydney NSW 2000, Sydney 6:00pm: Catering Enjoy Pizza and Beers. 6:30pm: Convolutional neural networks for text classification by Andy Huang Speaker Info: Andy currently heads artificial intelligence practice at Servian. He is also the organizer of Sydney Apache Spark User Group and an instructor on Apache Spark. He has extensive experience working with big data applications and large scale machine learning. 7:00pm: Deep Reinforcement Learning: An Introduction by Richard Xu Abstract: In this talk, Dr. Richard Xu will give a 15 minutes gentle introduction to the theories of Deep Q-Learning, with some background review of Reinforcement Learning (RL) for those unfamiliar with RL. Dr Xu will also demonstrate his student’s UTS Deep Learning Drone framework-in-progress. 7:20pm: "What’s new in Deep Learning and what’s next in our deep learning meet-up" Andy Zeng abstract: All the latest goodies in Deep Learning. 7:25pm: Announcement This is an announcement session for anyone to announce anything relates to deep learning and data science (e.g., hiring, new meetup, new startup). 7:30pm-8:30pm: Social Session We encourage people to stay and to socialize. We strive to make the meetup a real “meetup” event. In this session, we will serve drinks (alcohol and non-alcohol) and finger food till 8:30pm. So please stay and enjoy the night with hundreds of Deep Learners!

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  • 2017's First Deep Learning Sydney meetup at KPMG

    Time: 6pm – 8pm, Thursday 2nd March 2017 Location: Level 38, KPMG Sydney, Tower 3, International Towers Sydney, 300 Barangaroo Avenue, Sydney NSW 2000 6:00pm: Catering Enjoy Food and beverages. 6:20pm: Opening 6:25pm – 6:30pm: “Hello Alexa”, by Dr. Andy Zeng Speaker Intro: Dr Andy Zeng is the co-founder of Deep Learning Sydney, Associate Director of Data Science at KPMG, and Adjunct Associate at UTS. Abstract: This 5-minute talk will introduce how to launch the power of deep learning with Alexa, with a live demo. 6:30pm – 6:50pm: “Complex Event Processing and Machine Learning for near real time events”, by Gavin Whyte Speaker intro: Gavin Whyte, Director of Data Science, Analytics, Information and Modelling at KPMG, has over 25 years’ experience specialising in machine learning and software development. He is a seasoned Data Scientist, executive, leader and strategist an expert in business communications, product and process design relating to Data Science space. As a Director of Data Science for KPMG, and a machine learning specialist, he focuses on Data Science models for predictive capabilities. He has worn many hats in his career from software programmer, researcher, manager, strategist, technical reviewer for manning publications and Data Scientist. Abstract: The talk will go into complex event processing and functional programming with key focus on machine learning for near real time transactions. This type of application applies to varied use cases e.g., IOT, National Payments Platform, Fraud Detection, Network Analysis, Next best offer etc. Gavin will talk through the complexities of setting up a near real time framework and demo a tried and tested framework. 6:50pm – 7:10pm: "What goes on in the last layer of a neural network" by Dr. Richard Xu Speaker Intro: Dr Richard Xu is the Director of Industry Analytics and Visualisation at UTS, and co-founder of Deep Learning Sydney. He leads a group of 12 talented PhD students and engineers to apply our research and engineering skills to both Government and Retail insight analytics. In addition to cutting edge research, his group has also mastered modern data science tools, including Spark and TensorFlow. His series of Statistics, Probability and Machine Learning course is attracting PhD students all around the world. Abstract: The last layer of a network is typically the loss function: Each of them performs a different task. In this talk, Richard will briefly go over these loss functions, including Soft-max, Linear, Centre, Contrastive and Triplet. He will also illustrate some of the insights of different loss functions. This session will follow with a demo by Richard’s engineer. 7:10pm – 7:15pm: "What’s new in Deep Learning?" Dr Andy Zeng Abstract: All the latest goodies in Deep Learning. 7:15pm – 7:20pm: Announcement This is an announcement session. Anyone who would announce anything relates to deep learning and data science (e.g., hiring, new meetup, and new startup), please contact Andy for proper arrangement. 7:10pm: Catering Round 2 More food and drinks for our social session 7:20pm – 8:00pm: Social Session We encourage people to stay and to socialize. We strive to make the meetup a real “meetup” event. So please stay and enjoy the night with hundreds of Deep Learners!

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  • This the second Deep Learning Sydney meetup; another exciting and fun event!

    Agenda of Second Deep Learning Sydney Meet-up http://www.meetup.com/Deep-Learning-Sydney/ 7th/Sep/2016 Location: Level 9 Deloitte Sydney 6:00pm: Catering Enjoy Pizza and Beers. 6:30pm: Opening speech by Dr Ian Oppermann Speaker Intro: Ian has over 20 years’ experience in the ICT sector and, has led organizations with more than 300 people, delivering products and outcomes that have impacted hundreds of millions of people globally. He has held senior management roles in Europe and Australia as Director for Radio Access Performance at Nokia, Global Head of Sales Partnering (network software) at Nokia Siemens Networks, and then Divisional Chief and Flagship Director at CSIRO. Ian is considered a thought leader in the area of the Digital Economy and is a regular speaker on “Big Data”, broadband enabled services and the impact of technology on society. He has contributed to 6 books and co-authored more than 120 papers which have been cited more than 3200 times. Ian has an MBA from the University of London and a Doctor of Philosophy in Mobile Telecommunications from Sydney University. Ian is a Fellow of the Institute of Engineers Australia, a Fellow of the IEEE, a Fellow of the Australian Academy of Technological Sciences and Engineering, a Senior Member of the Australian Computer Society, and a member of the Australian Institute of Company Directors. Abstract: Data gives us a unique way to view the world and an ever more powerful lens to explore complex problems. Data with context is even more powerful, but brings with it specific challenges related to privacy and governance. By sharing examples of how NSW Government is utilising analytics, in particular the Deep Learning techniques, Dr Ian Oppermann will outline the practical ways that data analytics, machine learning and deep learning is being used to bring new and powerful insights. 6:50pm: “Introduction to Deloitte Deep Learning and Our Cognitive Technology Partner IPSoft by Andrew Muir and Raymond Lambie” Speaker intro: Raymond is the Senior Solutions Architect with IPsoft in Australia. With over 30 years in the IT industry, in roles spanning Mainframe Systems Programming to Cognitive Virtual Assistants, he brings a broad perspective on emerging technologies and their place in IT. Speaker intro: Andrew Muir leads the analytics practice in Sydney for Deloitte including strategy, implementation, modelling, machine learning and visualisation. His passion is in helping organisations to build analytical capabilities to deliver improved performance. Andrew is also leading the integration of cognitive technologies and methods including deep learning in the Australian practice. Abstract: Introducing the concept of Digital labour and Amelia, IPSoft’s Cognitive Virtual assistant. We will outline the technologies required to allow a Digital Employee to have a natural language conversation with the intent of servicing a customer request. 7:10pm: "A 15 minutes tutorial on Recurrent Neural networks" Dr. Richard Xu Abstract: In this talk, Dr. Richard Xu will give a 15 minutes gentle introduction to demystify Recurrent Neural network in a semi-mathematical way, and also include some live RNN demos. 7:30 pm: "What’s new in Deep Learning and what’s next in our deep learning meet-up" Dr Andy Zeng abstract: All the latest goodies in Deep Learning. 7:40 pm: Announcement This is an announcement session for anyone to announce anything relates to deep learning and data science (e.g., hiring, new meetup, and new startup). 7:45pm-9:00pm: Social Session We encourage people to stay and to socialize. We strive to make the meetup a real “meetup” event. In this session, we will serve drinks (alcohol and non-alcohol) and finger food till 9pm. So please stay and enjoy the night with hundreds of Deep Learners!

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