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21 May 2020
Global Online Live Conference (Time Zone - AEDT, Australia)

World Machine Learning and AI Business Strategy and Applications Day

Theme : Data Science, Deep Learning, Machine Learning and NLP
21 May 2020
Global Online Live Conference (Time Zone - AEDT, Australia)

World Machine Learning and AI Business Strategy and Applications Day

Theme : Data Science, Deep Learning, Machine Learning and NLP
21 May 2020
Global Online Live Conference (Time Zone - AEDT, Australia)

World Machine Learning and AI Business Strategy and Applications Day

Theme : Data Science, Deep Learning, Machine Learning and NLP
Ways to convince Your Boss Ways to Save

Briefly Know About This Event

World Machine and AI Business Strategy and Applications Day-2020, organized by 1.21GWs will focus on technical and practical verticals including use cases around Real-time analytics, AI regulations, NLP, Machine Learning and Deep Learning . AI, Machine Learning and Deep Learning is Re-inventing.

Don’t get left behind.

Designed specifically for executives, business leaders, and strategists, the APAC AI Business Day provides concise, high-level executive briefings on the most promising and important developments in AI for business.

You’ll get an insider’s look at the AI implementations that will have the most profound impact on your business. Advice on how to mitigate risk and out-innovate your competitors. Detailed case studies of successful AI projects.

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

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Conference Schedule (21st May, 2020)

X Topic Abstract

Confusion exists everywhere, especially when we discuss artificial intelligence, machine learning and now deep learning is added to this list.
Deep learning is the next layer of applying intelligence on machines to help humans live better lives, ensure an exceptional experience when working with digital tools and even navigate unknown lands with just a smartphone and some apps on it.
Let us use this time to unpack machine learning, deep learning and what innovations have been applied and how they are benefiting healthcare, finance, retail, and other consumer needs.
The purpose of this session would be to explore the innovations in deep learning and machine learning. We will use methods such as analyzing the example solutions from each of these verticals to highlight the specific deep learning methods such as neural networks and speech recognition."

X Topic Abstract

One of the earliest and most successful use cases of machine learning has been helping users to discover new content and discover related or new products and services. Machine learning algorithms can help customers discover new content based on previous viewing behaviour (the Netflix model) and new / related products based on previous purchases (The Amazon model). However, algorithms that target the challenge of discoverability have typically only worked well where customer behaviour is static or only changes slowly, such as movie and book recommendations. More recently, advances in machine learning algorithms have enabled recommending items that do not meet these criteria. In this talk, I will first discuss the conceptual problems of applying machine learning to the discovery of time sensitive material and products. I will then discuss how recommendation algorithms can be adapted to solve these problems. Finally, I will share how we applied machine learning to the challenge of discoverability in OVOPlay - a sports streaming service that has had to overcome the challenge of limited metadata, a broad ranges of customers and a range of products from telco to entertainment.

Speaker Profile

X Topic Abstract

Matt is joining us today to talk about how the rapidly changing exponential times we are living in provide opportunities, and new risks, for BHP, illustrated with plenty of war stories. Matt will focus on a new PwC global offering he has been leading the development of : Responsible A.I. Concerns have grown over how artificial intelligence (AI) could impact privacy, cybersecurity, employment, inequality and the environment. Customers, employees, boards, regulators and businesses are all asking the same question: can we trust AI? Stakeholders want to know that organisations are using AI responsibly, so that it strengthens the business and society as a whole. PwC’s recently released Responsible AI Framework and Toolkit helps companies focus on and address the challenges and risks around AI when designing and deploying AI applications. Please consider completing the free diagnostic available at pwc.com/rai before attending this presentation.

Speaker Profile

Professor Matt Kuperholz is the PwC Australian firms Chief Data Scientist, was voted Australia's top analytics leader as awarded by the premier industry body, has been awarded top 50 Data Leaders on the planet and top 100 Knowledge Workers in Australia by the office of the Chief Scientist and the Prime Minister. Matt is a self confessed major computer geek who has been applying A.I. in anger to real world client problems most days this millenium.

X Topic Abstract

"What technology and trade have done ... is displace Australian workers from their middle-class jobs, and send them hurtling down the income ladder into less remunerative occupations ... The plight of the downward mobile manufacturing worker is familiar to most Australians. But that of the displaced administrative assistant is less so. And yet, they are two sides of the same story... What are these jobs like with automation and AI?

Speaker Profile

Lucio is involved with lecturing and research in Academia in Australia. He is currently: Sessional lecturer in Digital Marketing at RMIT Mentor in A.I. at Future Skills at RMIT Sessional lecturer in Marketing Data and Insights for the Faculty of Business and Law at Deakin University. 20 years in Marketing and Advertising. Lucio has worked with companies like Mercedes-Benz, Unilever, P&G, Renault, Target, Parmalat, Cadbury, Mondelez and more.

X Topic Abstract

I will be talking about the AI and team augmentation. I will provide practical examples of how this can be achieved. Process automation and where to start. Automation doesn't start at AI. At the same time, data reach companies require the right strategy to see practical real-time insights into their business - that gives them a competitive advantage and also focus on what they do differently.

Speaker Profile

Basyrov is an experienced investor and serial entrepreneur, applying creative and technology-forward data and digital solutions across a large cross section of industries to solve complex challenges. He sits on the board of advisors to Forbes AI and ASX listed company Opyl.ai. He also made his first million dollars at the age of 26 by investing in the stock market. As a CEO of Edway Apps Studio and Intelligent Profit Solutions, Basyrov has designed and developed more than 80 enterprise solutions and startup projects. Over the years, Basyrov has built a broad high-value professional network of developers, investors and collaborators across the globe. He holds a Bachelor of Business in Accounting and Management from Central Queensland University and is a Certified Practicing Accountant (CPA Australia).

X Topic Abstract

• AI is not software development – it is research
- How does this impact companies whose IT department are used to having clear requirements and outcomes
- How should organisations begin their AI journey
- The traps most organisation face when starting up AI in their business
• What are the problems you are trying to solve with AI?
- Automate human repetitive tasks
- Better Decision-making using intelligent analytics
- Improve health and safety
- Compliance

• Data is King – but so is the ability to build a solution
- Understanding the business problem, not just the data
- Fail-Fast theory

• Everyone forgets about deploying AI
- What are the key issues for IT organisations?
- Data Scientists and Operational systems – what are the challenges
- Creating a digital twin to deploy
- Reliability, scalability and cost

X Topic Abstract

Data wrangling, data munging, or data transformation, the part of the Data Science Process sitting in between data acquisition and exploratory data analysis (EDA) is one of the core requirement of any AI or data science project. It includes a set of tasks you have to perform in order to understand your data and prep it for machine learning. The story has been told many times, that the data wrangling process can take up a sizable percentage of the time spent on the project by the data scientist, often reported as high as 75%.

Many may dismiss the role of a data wrangler as ordinary custodial work, but when done properly, it can help lead to accurate insights based on valuable enterprise data assets. The first step, however, is to make sure you data wrangling skills are up to snuff. In this talk I will be discussing some of the make-or-break data wrangling skills you’ll need for successful AI projects.

Speaker Profile

Bhavika believes in working towards a better world through data. Information Management professional with fifteen years’ experience of complex information environments spanning the full spectrum of structured data to unstructured information. Eloquent and influential communicator, adept at stakeholder management at all levels of the organisation, across multiple business lines, shared services, third parties and vendors. Proven business acumen with demonstrated results to deliver enhanced customer experience and increased business profitability. Deep technical knowledge of multiple specialisms including metadata, data warehousing, data governance, data quality, enterprise architecture, data lineage, Big Data, data analytics, and regulatory requirements. Bhavika is big advocate of encouraging more women in data, she mentors young girls, female who are keen in progressing their career as data professionals. In free time, she teaches, likes to read, travel and teach young kids.

schedule 08:45AM – 09:00AM Login/ Conference Overview
schedule 09:00AM – 09:45AM Innovations in machine learning and deep learning - Click Here for More Info
Rama Ravindranathan,Director of Product Management, UnitedHealth Group

schedule 09:45AM – 10:30AM Content discovery and recommendations for time sensitive content - Click Here for More Info
Henrik Petander, Head of Artificial Intelligence and Machine Learning, Sourse

schedule 10:30 AM – 11:00 AM Break
schedule 11:00AM – 11:45AM RESPONSIBLE AI : with great power comes great responsibility - Click Here for More Info
Professor Matt Kuperholz, Chief Data Scientist, PwC

schedule 11:45AM – 12:30PM Impact of AI on Workforce - Click Here for More Info
Lucio Ribeiro, Lecturer, lucio.AI

schedule 12:30PM – 01:30PM Lunch Break
schedule 01:30PM – 02:15PM AI is my copilot - Click Here for More Info
Marat Basyrov, AI Executive Advisory Board, Forbes | CEO, Adevi.io

schedule 02:15 PM – 03:00PM AI is science, not programming - Click Here for More Info
Vinnie (Arvin) Amir, Founder, systemize.ai

schedule 03:00 PM 03:30 Break
schedule 03:30PM – 04:15PM Data Wrangling - Click Here for More Info
Bhavika Unnadkat, Head of Data, Momentum Energy

Register Your Attendance At Conference 2020

Any Question? Call: +919810667556

Ticket Price & Plan

Standard Price

AUD 349

Till 21st May, 2020

Conference ticket

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USA - +1 908 444 0221

India - +919810667556


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