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03 December, 2021

Data Lake, Analytics & Machine Learning Summit - ANZ


Global Online Live Conference
All time mentioned in Melbourne Time Zone



03 December, 2021

Data Lake, Analytics & Machine Learning Summit - ANZ


Global Online Live Conference
All time mentioned in Melbourne Time Zone



03 December, 2021

Data Lake, Analytics & Machine Learning Summit - ANZ


Global Online Live Conference
All time mentioned in Melbourne Time Zone



Ways to convince Your Boss Ways to Save

Briefly Know About This Event



Our hearts and thoughts remain with those affected by the COVID-19 outbreak worldwide. In the past months,1point21GWS has been organizing conferences on Virtual platform.

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.

Agenda: 03 December , 2021
Track 1 : Tools, APIs & Frameworks
Track 2 : Applications/Use Case


  • 20+

    Global Speakers

  • 20+

    Topics

  • 2

    Tracks

  • 1

    Day Conference

Conference Schedule (03 December, 2021)

Track 1 : Tools, APIs & Frameworks
Track 2 : Applications/Use Case

( All time mentioned in Melbourne Time zone )

X Topic Abstract

One of the most important skills for those who work with Machine Learning (ML) is to know which method is the right choice for a given problem. Some choices are trivial however, there is usually a myriad of algorithms that can be used. In addition, productionising a trained model also comes into the production-level pipeline. Modern end-to-end (E2E) learning refers to the entire pipeline of a production-level ML application. This usually consists of infrastructure architecture, data processing, statistical modelling, ML frameworks, distributed computing, deployment as well as user experience (UX). In this talk, we are explaining the journey of a Data Scientist with their required skills/knowledge. What does a full stack hands-on mean? How can Data Scientists or a ML Engineers improve their skill sets to make themselves a contributor in the modern E2E ML product development? These are some of the most important questions data scientists have. We are going to make a clear picture of this journey by demonstrating a real-life customer pattern recognition use case.,

X Topic Abstract

Preserving privacy when processing data from multiple sources with machine learning is always a challenge. Organizations may want to perform collaborative data analytics while guaranteeing the privacy of their individual datasets. Combining multiple data sources to support a better algorithmic outcome improves accuracy of prediction, but it may come at cost of confidentiality, if sensitive information is not accurately protected.
Azure Confidential Computing adds new data security capabilities to the cloud and specifically to machine learning processing. By using trusted execution environments (TEEs) to protect your data while in use, with confidential computing, you can use machine learning algorithms across different organizations to better train models, without revealing the processed data.
This session presents the benefits of Azure Confidential Computing in an ML scenario, where two separate health institutes collaborate on data analysis and prediction using Azure Machine Learning, and still mask any sensitive information to protect the privacy of their patients.
A session about protecting data in the cloud with confidential computing.
The use case is for organisations to share data with full confidentiality protection.

X Topic Abstract

I will explain how the modern digital company is aproaching digitalization, will give examples and tips how to achive fast growth and retain customers. I will then demo a brain storming session with real time planning interactive board on how to lunch digital product and calculate budget and model process of customers uptake.



Speaker Profile

Nikola is the SVP, Chief Data Scientist at PT Smartfren Telecom. He leads data analytics and data science projects from strategy development, execution to delivery with regard to the collection, manipulation and AI based analysis of data for various business functions and departments including customer experience, customer on-boarding, marketing, sales, network operations etc.

X Topic Abstract

The talk introduces how AI and big data analysis can be used in the aged care sector. We have always been committed to using AI to help improve the welfare system and the standard of living of residents - particularly senior citizens. We invented CaptureLive, a smart care solution for the elderly with innovative patented fall prevention and detection system driven by ML&AI, for families of elderly people who can monitor seniors' status and send alerts to carers when a fall is predicted to occur.

Speaker Profile

Taicheng is the CTO of AIBUILD PTY LTD, an innovative Australian startup company that develop solutions using state-of-the-art technology from AI, VR to IoT with Australian Innovation Patent granted.

X Topic Abstract

The physical infrastructure underpinning large scale machine learning workloads is moving from traditional architectures to innovative new designs in the data centre. These new, and often radical, physical designs reduce energy consumption and increase density, which allows machine learning workloads to scale at lower cost and with little or no environmental impact.



Speaker Profile

Peter is a project leader and systems architect who specialises in cloud computing, machine learning and software engineering. He's particularly passionate about building scalable and robust technology with high usability. Peter began his career in financial services where he designed and developed institutional banking systems for major Australian and international banks including Westpac, the Commonweath Bank, NAB, HSBC, and the Bank of Tokyo. Peter later moved into the e-research sector where he initiated and led big-data and cloud computing projects at the Tasmanian Partnership for Advanced Computing (TPAC), the Integrated Marine Observing System (IMOS), and the Australian Ocean Data Network (AODN). Peter has worked in the startup space where he designed machine learning systems for fin-tech and other technology businesses including Biteable. Peter holds a PhD in artificial intelligence along with a Masters degree in accounting and a Bachelors degree in computer systems engineering. Peter lives in Hobart. He likes dogs, although he doesn't have one, and is warming to cats.

X Topic Abstract

Deep learning is driving advances in artificial intelligence that are changing our world. Computer vision gives machines those eyes to detect, track, classify and analyse objects while feeding with images and videos.
In this presentation, we'll talk about some ground breaking applications implemented worldwide using computer vision and have a small demo on how to detect a face in a video.

X Topic Abstract

Speaker Profile

X Topic Abstract

Computer vision applications are expected to grow at an estimated market size of $28bn by 2030. Many companies have started to realize the potential benefit AI can bring to their organization.
In this session, we will have a brief introduction to the applications of Visual inspection and other use cases in video analytics and action recognition.



Speaker Profile

Gomathy shankar is a Senior Data scientist in IBM, Singapore. He has worked on multiple AI/ML products, working closely with the clients and making them successful in their digitization journey.

X Topic Abstract

HyperAutomation will become the "Next Normal" for addressing all the "Digitization" and "Digital Automation" need where organizations are shifting to consume more impactful integrated HyperAutomation technologies to have an array of tools such as RPA, AI, ML, Analytics, Process Mining, iBPMS and associated skills to situationally apply as needed. It’s important for organizations, business and IT stakeholders to understand how "HyperAutomation" suite products act as powerful catalyst for product standardization, product differentiation and paving the way towards becoming "Digital First Organization" which is the highly pervasive to sustain, grow and prevail in the current Digital Era. Also, all such “Digital First” organizations will have to adopt Digital product management to build scalable, responsive, and resilient products that can sustain and prevail in all socio-economic conditions.

Speaker Profile

Raghav Nyapati is the Senior Director – Product Head of Digital Automation (RPA, AI, and ML) at ASG Technologies. Founder and Creator (Head of Automation) of Robotics Automation and Cognitive Automation Product (ASG-Zenith) which provides best-in class HyperAutomation platform for customers. He is creator of “Digital Product Life Cycle (DPLC)” framework and approach that can be used to build new “HyperAutomation” products, scale and grow existing digital products which has been adopted in various customers and industries such as Banking, Insurance, Healthcare, Retail across various the globe.
Raghav is recognized as an Industry Ambassador and Digital Automation expert in Robotic Process Automation, Cognitive Automation (complementing AI skills such as NLP, CV with RPA) providing mentoring, coaching, and evangelizing digital automation products to various premier B Schools, Product Schools and Engineering institutes across the globe.


Raghav has authored, published, and presented many articles, journals, podcasts on HyperAutomation, Robotics, AI, and Cognitive Automation in various platforms such as Medium, CIO Magazine, TechTarget publication etc. Raghav has filed Patent on “Unified Digital Automation Platform- RPA + BPM” (9804US) which is registered in US Patents Office in 2021.
Raghav is a Keynote Speaker and Industry Delegate presenting in various Webinars, conferences, summits, and educational forums/institutes on HyperAutomation products such as RPA, AI, and ML.
X Topic Abstract

Speaker Profile

X Topic Abstract

Speaker Profile

schedule 08:30AM - 09:00AM 08:30AM - 08:50AM : Login / Registration
08:50AM - 09:00AM : Conference Overview
Abhilasha Sinha, Director- Summits, 1.21GWS
speaker
09:00AM - 09:40AM Keynote

schedule 09:40AM - 10:20AM Break
speaker
speaker
10:20AM - 11:00AM Track 1 : On Modern Data Science Model Development - Delta Lake from Feature Generation to ML Model Monitoring and Retraining. - Click Here for More Info
Payam Mokhtarian, Principal Data Scientist, Tabcorp
Track 2 : Secure multiparty Machine Learning with Azure Confidential Computing . - Click Here for More Info
Stefano Tempesta, Senior Program Manager - Azure Confidential Computing, Microsoft
speaker
speaker
11:00AM - 11:40AM Track 1 : AI + big data usage in the aged care sector - Click Here for More Info
Taicheng Zhou, CTO & Chief Scientist,AIBUILD PTY LTD
Track 2 : Using ML and AI for customers digital growth and retention in Telecom . - Click Here for More Info
Nikola Sucevic, SVP Data Analytics, PT Smartfren Telecom
speaker
speaker
11:40AM - 12:20PM Track 1 : Image and object detection - Click Here for More Info
Pankaj Gabale, Data Scientist,EY Analytics (Asia-Pacific)
Track 2 : Energy Efficient Machine Learning. - Click Here for More Info
Dr Peter Blain, Director of Machine Learning and HPC, Firmus
speaker
speaker
12:20PM - 01:00PM Track 1 : HyperAutomation - Rethink the Future of Work - Click Here for More Info
Raghav Sanjeev Nyapati, Senior Director- Digital Automation Leader,Rocket-ASG Software
Track 2 : Visual Inspection and Action recognition. - Click Here for More Info
Gomathy shankar, Senior Data Scientist, IBM
schedule 01:00PM - 02:00PM Break
speaker 02:00PM - 02:40PM Track 1 : Image & Object Recognition

Track 2 : Automatic Translation & Caption Generation
speaker
02:40PM - 03:20PM Track 1 : Applying Machine Learning Online at Scale

Track 2 : Visual Inspection & Action Recognition
schedule 03:20PM - 04:00PM Break
speaker 04:00PM - 04:40PM Track 1 : Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning

Track 2 : Speech, Gesture & Character Recognition

Conference Ticket Price & Plan

Early Bird

AUD 249

Till 03 November, 2021

Group of 3 or more

AUD 299

Till 03 December, 2021

Individual (Standard Price)

AUD 399

Till 03 December,2021





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FAQs

• 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
Understand the state of development of Machine learning by exchanges, clearing houses, central counter parties and payment systems, and what it means for you.
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.
Best practices while attending online conference:
Login to your system with the login detail 10 minutes prior to the start time
Should be connected to a good network to avoid interruptions.
Should be at a quiet place while taking your session.
Ensure all other windows are closed and no application is running. This will ensure good audio and video quality
Mute yourself if not expected to speak
Do ask the question via chat box to keep the session lively. You can Ask questions
Yes, all conference attendees must register in advance to attend the event.


Register Your Attendance At Conference 2021

Any Question? Call: +91 9810667556