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Overview of the event

Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to "learn from data, without being explicitly programmed.

The "deep" in "deep learning" refers to the number of layers through which the data is transformed. Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to its original goals. In deep learning, each level learns to transform its input data into a slightly more abstract and composite representation.



Facts & Figures About The Event

7 Speakers
7 Topics
50 Tickets

Conference Schedule

Machine learning and Deep Learning Day (28th November, 2019)

X Topic Abstract

Vishal will be talking about the disruption in the space of Risk Management and how data analytics can be used in this space to enhance the existing risk management practices. The discussion will also include best practices to embed data analytics capabilities within the different risk functions.


X Topic Abstract

Jens will demonstrate how easy it is to use Machine Learning and Keyword Classification to extract information from Invoices and Receipts without using templates.


X Topic Abstract

One of the main challenges facing the data science community is that their ML models are not built with production in mind. Hence most models do not end up being deployed as production quality code but rather stay in ad-hoc scripts or notebooks. I'll share my experience of how I have built low latency machine learning applications at scale.


X Topic Abstract

Credit risk analysis has become more complex due to increasing availability of data and the need to take into account customer and market specific factors. Using state-of-the-art data science technologies can augment the traditional credit risk analysis, as demonstrated by this case study. The machine learning model produces estimated probabilities of default for individual loans, based on which credit scores can be calculated. With more efficient management of credit risks, lenders can become more nimble and improve their competitive edges

Speaker Profile

Dr Zhu has a PhD degree in Electrical and Electronics Engineering. She has worked in academics/government organisation and private industries. She is passionate about solving financial problems and helping financial firms gain their data advantages.


X Topic Abstract


X Topic Abstract

Bayesian machine learning has been growing in popularity because of a number of theoretical and technological advancements. In this talk we will give a brief overview of the stepping stones from standard machine learning approaches to Bayesian approaches. We will talk through the features that its proponents admire and the problems that have been holding Bayesian approaches back from widespread adoption.


X Topic Abstract

Regulation and legal domain had long been untouched by modern technology due to its intricate and detail-oriented nature. With the advent of machine learning, the norm is being challenged and new terms such as RegTech and LegTech are born. In this talk, I will be talking about how machine learning has changed the compliance industry in recent years. This talk will touch down on aspects such as application of machine learning to detect compliance breaches using natural language processing and computer vision, and will be catered for an ensemble of technical, non-technical and business leaders alike.

Speaker Profile

Gitansh leads the machine learning practice at Red Marker - AI Powered compliance, which is a Sydney-based RegTech company. Previously, he has worked as a data scientist and academic researcher on Australian Research Council project at Monash University in Melbourne. He has also worked at IBM and Honeywell previously. He holds a masters (by research) in data science and machine learning from the University of Melbourne. He also has a bachelor degree (Hons) in engineering. He was the Richard E. Merwin scholar and IEEE Computer Society Ambassador for Australia in 2016.


X Topic Abstract


X Topic Abstract

This presentation would be about how we can leverage Apache Kafka and it's components to train, apply ML model and predict in real time streaming manner. Transformation from traditional batch oriented way to stream processing approach to Machine Learning with Apache Kafka and Kstream API.

Our Sponsors

Use this opportunity to improve the visibility of your organization

Instant Sponsorship
Avail instant sponsorship at just USD 2000

Instant sponsorship includes
• Branding of your company as Bronze Sponsor – Company's Logo on the event page with cross link to your website.
• One Speaking Slot (45 min -non sales talk).
• 10% discount on registration fee for any delegate from your organization.
• Full day attendance at the event with lunch
• 1 x Roll up stand / Brochure distribution at the event
• Online Interview post of your company's senior executive at our media portal

For Silver, Gold Platinum & Titanium Sponsorship opportunites, please request for Sponsorship Brochure via email at contact@1point21gws.com, naveen@1point21gws.info

Our Sponsors


Media Partners


               




Our Speakers


Kanishka Mohaia

Head of Data and Optimisation

Rokt


Abhijit Kumar

Data Architect

Deltatre


Gitansh Khirbat

Machine Learning Engineer

RedMarker (Kaplan)


John Hawkins

Data Scientist

DataRobot


Jens Pistorius

RPA Evangelist and CEO

Incepto


Vishal Kapoor

Director, Data & Analytics

INGRITY


Pavel Gimelberg

Principal, Head of Intelligent Automation Practice APAC

EPAM Systems


Dr Qian Zhu

Data Science Consultant

Foresight Analytics


Bilal Farooq

Principal Data Scientist

Teradata

Want to become Speaker Please register here Register

Our Pricing

Group of three or more(Early Bird)

AUD 362

Till July 27
Group of three or more(Standard)

AUD 434

Till November 28
Individual(Early Bird)

AUD 577

Till October 28
Individual (Standard)

AUD 722

Till November 28


Our Testimonial

FAQs

Who can attend Machine learning and Deep Learning Day in Sydney?

• Data Engineers/Developers / Scientists
• Analytics Professionals
• Startup Professionals
• Scientists/Researchers
• Professors
• President/Vice president
• Chairs/Directors

And last but not the least……….
Anyone interested in Machine Learning & thrives to make the future developed and better

Why to attend Machine learning and Deep Learning Day in Sydney?

Understand the state of development of Machine learning by exchanges, clearing houses, central counter parties and payment systems, and what it means for you.

What will you learn about?

Detecting where underlying problems and frictions exist in your organisation that will be alleviated by Machine learning technologies. Using Machine learning as a tool for innovation across your organisation

Are there any prerequisites to attend this program?

No

Do I need to register for the event?

Yes, all conference attendees must register in advance to attend the event.