Explainable AI for Financial Services

machine-learning-&-deep-learning Workshop 45 Mins Advanced
Prabhash Thakur
Prabhash Thakur
Director, Data Science
Centelon

Centelon develops AI based decision systems for financial services. One of the key regulatory requirements is to explain the model to the authorities. We have deployed multiple methods such as Local Interpretable Model Agnostic Explanations (LIME) and Game theory based Shapley Values.

In the talk, I would take the audience through the business case, mathematics behind various explanatory models, design considerations and code demonstration

 
7 favorite thumb_down thumb_up 2 comments visibility_off  Remove from Watchlist visibility  Add to Watchlist
 

Outline/Structure of the Workshop

1. Need for explainable AI in Financial Services

2. Two Approaches: Node explanations versus Feature Importance

3. Model specific explanation methods in NLP

4. Model Agnostic Methods a) Drop-one-feature method and its limitation

5. Model Agnostic Methods b) Theoretical background of LIME and its limitations

6. Model Agnostic Methods c) Theoretical background of Shapley Values

7. Equivalence conditions for Shapley Values and LIME

8. Code Demo: ( Financial Services use case, None Financial Services use case)

Learning Outcome

The audience will begin to appreciate the need for building explainable systems. They would learn the basic tool set to deploy in various use cases.

Target Audience

Developers, Executives

Prerequisites for Attendees

Basic Machine Learning, Deep Learning

Links

https://www.youtube.com/watch?v=bi4b9LXWrlo

https://www.youtube.com/watch?v=iArxz7Flf8w

https://www.youtube.com/watch?v=V_UazN5Whvw

 

schedule Submitted 4 months ago

Public Feedback

comment Suggest improvements to the Speaker
  • Dr. Vikas Agrawal
    By Dr. Vikas Agrawal  ~  2 months ago
    reply Reply

    Dear Prabhash: I was trying to locate your LinkedIn profile and your bio on confengine.com. Could you please add those?

    We have two other proposals submitted on a very similar topic and so we are considering those as well.

    Warm Regards

    Vikas

    • Prabhash Thakur
      By Prabhash Thakur  ~  2 months ago
      reply Reply
      Hi Vikas - Thank you for your email. We recently connected on LinkedIn. My linkedin profile is www.linkedin.com/in/prabhash-thakur. I will update it on confengine as well.

      Best Regards,
      Prabhash Thakur

      --000000000000a5fff6058a142f62--

People who liked this proposal, also liked:

  • Liked Vivek Singhal
    keyboard_arrow_down

    Vivek Singhal / Shreyas Jagannath - Training Autonomous Driving Systems to Visualize the Road ahead for Decision Control

    4 data-science-learnathon Accepted Workshop 90 Mins Intermediate fcn deeplab semantic-image-segmentation autonomous-driving self-driving-cars unet espnet computer-vision convolutional-neural-networks image-processing
    Vivek Singhal
    Vivek Singhal
    Co-Founder & Chief Data Scientist
    CellStrat
     Shreyas Jagannath
    Shreyas Jagannath
    AI researcher
    Cellstrat
    schedule 1 month ago
    Sold Out!
    90 Mins
    Workshop
    Intermediate

    We will train the audience how to develop advanced image segmentation with FCN/DeepLab algorithms which can help visualize the driving scenarios accurately, so as to allow the autonomous driving system to take appropriate action considering the obstacle views.

    4 favorite thumb_down thumb_up 0 comments
    View Details play_arrow
  • Liked Vivek Singhal
    keyboard_arrow_down

    Vivek Singhal / Anshumaan Dash / Anupam Ranjan / Shreyas Jagannath / Shubha Manikarnike - Advanced AI Application Showcase

    19 machine-learning-&-deep-learning Workshop 480 Mins Intermediate computer-vision image-segmentation image-processing pose-estimation densepose u-net deeplab natural-language-processing bert ner neural-language-translation sequence-models time-series reinforcement-learning driverless-cars morphnet neural-networks convolutional-neural-networks recurrent-neural-networks artificial-intelligence ai-research gaming text-analytics healthcare
    Vivek Singhal
    Vivek Singhal
    Co-Founder & Chief Data Scientist
    CellStrat
     Anshumaan Dash
    Anshumaan Dash
    Deep Learning Researcher- Computer Vision
    CellStrat AI Labs
     Anupam Ranjan
    Anupam Ranjan
    -
     Shreyas Jagannath
    Shreyas Jagannath
    AI researcher
    Cellstrat
     Shubha Manikarnike
    Shubha Manikarnike
    Deep Learning Researcher
    Cellstrat AI Lab
    schedule 3 months ago
    Sold Out!
    480 Mins
    Workshop
    Intermediate

    In this session, data scientists from CellStrat AI Lab will present demos and presentations on cutting-edge AI solutions in :-

    • Computer Vision - Image Segmentation with FCN/UNets/DeepLab/ESPNet, Image Processing, Pose Estimation with DensePose
    • Natural Language Processing (NLP) - Latest NLP and Text Analytics with BERT, NER, Neural Language Translation etc to solve problems such as text summarization, QnA systems, video captioning etc.
    • Reinforcement Learning (RL) - Train Atari Video Games with RL, Augmented Random Search, Deep Q Learning etc. Apply RL techniques for gaming, financial portfolios, driverless cars etc. Train Robots with MuJoCo simulator.
    • Driverless Cars - Demo on multi-class roads datasets, path planning and navigation control for cars etc.
    • Neural Network Architectures - Faster and Smaller Neural Networks with MorphNet
    19 favorite thumb_down thumb_up 2 comments
    View Details play_arrow
  • Liked Vivek Singhal
    keyboard_arrow_down

    Vivek Singhal - Advances in Reinforcement Learning

    20 machine-learning-&-deep-learning Talk 45 Mins Intermediate reinforcement-learning policy-gradients q-learning td-learning markov-decision-processes value-iteration-algorithm bellman-equation openai-gym rewards-based-learning
    Vivek Singhal
    Vivek Singhal
    Co-Founder & Chief Data Scientist
    CellStrat
    schedule 3 months ago
    Sold Out!
    45 Mins
    Talk
    Intermediate

    This session will discuss Reinforcement Learning (RL) algorithms such as Policy Gradients, TD Learning and Deep-Q Learning. We will discuss how emerging RL algorithms can be used to train games, driverless cars, financial decision models and home automation systems.

    20 favorite thumb_down thumb_up 2 comments
    View Details play_arrow
Recent Activities
Call for Proposals CLOSED
Ended on Apr 15 '19 11:30 PM IST
Speaker Compensation
flightTravel covered info_outline
hotelAccommodation covered info_outline
confirmation_numberFree conference pass info_outline
Please refer to our Speaker Compensation Policy
Active Members