The talk will cover how Chaos and Fractals are connected to machine learning. Artificial Intelligence is an attempt to model the characteristics of human brain. This has lead to model that can use connected elements essentially neurons. Most of the biological systems or simulation related developments in neural networks have practical results from computer science point of view. Chaos Theory has a good chance of being one of these developments. Brain itself is an good example of chaos system. Several attempts have been made to take an advantage of chaos in artificial neural systems to reproduce the benefits that have met quite a bit success.

 
 

Outline/Structure of the Talk

1. Introduction of Chaos

2. How Chaos relates to AI

3. Future of Chaos/AI

4. Applications

Learning Outcome

Understanding of Chaos,

Connection between Chaos and Machine Learning,

How future of Machine Learning can be Chaos!

Target Audience

Data Mining experts

schedule Submitted 2 years ago

Public Feedback


    • Sohan Maheshwar
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      Sohan Maheshwar - It's All in the Data: The Machine Learning Behind Alexa's AI Systems

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      Sohan Maheshwar
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      schedule 2 years ago
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    • Santosh Vutukuri
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      Santosh Vutukuri - Embedding Artificial Intelligence in Spreadsheet

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    • Joy Mustafi
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      Joy Mustafi - The Artificial Intelligence Ecosystem driven by Data Science Community

      Joy Mustafi
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      schedule 2 years ago
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    • Dr. Savita Angadi
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      Dr. Savita Angadi - Connected Vehicle – is far more than just the car…

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      schedule 2 years ago
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    • Dr. Rohit M. Lotlikar
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      Dr. Rohit M. Lotlikar - The Impact of Behavioral Biases to Real-World Data Science Projects: Pitfalls and Guidance

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      Data science projects, unlike their software counterparts tend to be uncertain and rarely fit into standardized approach. Each organization has it’s unique processes, tools, culture, data and in-efficiencies and a templatized approach, more common for software implementation projects rarely fits.

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    • Srijak Bhaumik
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      Srijak Bhaumik - Let the Machine THINK for You

      Srijak Bhaumik
      Srijak Bhaumik
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      schedule 2 years ago
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      Every organization is now focused on the business or customer data and trying hard to get actionable insights out of it. Most of them are either hiring data scientists or up-skilling their existing developers. However, they do understand the domain or business, relevant data and the impact, but, not essentially excellent in data science programming or cognitive computing. To bridge this gap, IBM brings Watson Machine Learning (WML), which is a service for creating, deploying, scoring and managing machine learning models. WML’s machine learning model creation, deployment, and management capabilities are key components of cognitive applications. The essential feature is the “self-learning” capabilities, personalized and customized for specific persona - may it be the executive or business leader, project manager, financial expert or sales advisor. WML makes the need of cognitive prediction easy with model flow capabilities, where machine learning and prediction can be applied easily with just a few clicks, and to work seamlessly without bunch of coding - for different personas to mark boundaries between developers, data scientists or business analysts. In this session, WML's capabilities would be demonstrated by taking a specific case study to solve real world business problem, along with challenges faced. To align with the developers' community, the architecture of this smart platform would be highlighted to help aspiring developers be aware of the design of a large-scale product.

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      a - Building a Feature Platform to Scale Machine Learning at GO-JEK

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      a
      a
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      schedule 2 years ago
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      45 Mins
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      Go-Jek, Indonesia’s first billion-dollar startup, has seen an incredible amount of growth in both users and data over the past two years. Many of the ride-hailing company's services are backed by machine learning models. Models range from driver allocation, to dynamic surge pricing, to food recommendation, and process millions of bookings every day, leading to substantial increases in revenue and customer retention.

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    • Dr. Veena Mendiratta
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      Dr. Veena Mendiratta - Network Anomaly Detection and Root Cause Analysis

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    • Saibal Dutta
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      Saibal Dutta - A Multi-criteria Decision Making Approach and its Applications in Business

      45 Mins
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      Intermediate

      We live in a world of information where decision takes a very important role. Human are considered one of the best species since we like to think and quantitatively analysis our decision process based on the available information. But the question may arise:


      1. How can we take a right decision or mathematically, optimal solution among the multiple alternatives?


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      2. How to minimize the risk and define in mathematically for a given business problem?


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      3. How to apply TOPSIS methods to design and solve any practical business problem?


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