schedule Sep 2nd 10:00 AM - 06:00 PM place Mars people 17 Interested add_circle_outline Notify

You have been hearing about machine learning (ML) and artificial intelligence (AI) everywhere. You have heard about computers recognizing images, generating speech, natural language, and beating humans at Chess and Go.

The objectives of the workshop:

  1. Learn machine learning, deep learning and AI concepts

  2. Provide hands-on training so that students can write applications in AI

  3. Provide ability to run real machine learning production examples

  4. Understand programming techniques that underlie the production software

The concepts will be taught in Julia, a modern language for numerical computing and machine learning - but they can be applied in any language the audience are familiar with.

Workshop will be structured as “reverse classroom” based laboratory exercises that have proven to be engaging and effective learning devices. Knowledgeable facilitators will help students learn the material and extrapolate to custom real world situations.

 
 

Outline/Structure of the Workshop

  • Representing Data with Models. Use of functions and parametric functions to build models.
  • Model Complexity, what is Learning from a Computational point of view. How does a Computer learn?
  • Exploring Data with Unsupervised Learning, Dimensionality reduction for Image Classification.
  • Applications using Unsupervised Machine learning
  • Introduction to Supervised Machine Learning
  • Practical Applications using Supervised Machine Learning, (Object detection etc.)
  • Introduction to Neurons, Learning with a Single Neuron
  • Introduction to Flux.jl, learning with a single neuron using Flux
  • Introduction to Neural Networks, Building single layer neural net with Flux
  • Introduction to Deep Learning, Multi-Layer Neural Network with Flux
  • Handwritten recognition with neural networks

Learning Outcome

  • Participants will walk away feeling comfortable with machine learning and the underlying algorithms.
  • Participants can consider themselves not as consumers of APIs of various ML libraries, but can become comfortable with building the underlying algorithms in Julia and be able to contribute to various ML packages and in general to Julia too!

Target Audience

Aspiring Data Scientists, experienced data scientists who are eager to get better understanding of the implementation of ML algorithms.

Prerequisites for Attendees

  1. Not to shy away from getting into some mathematical concepts

  2. Commitment to strive towards understanding the concepts and program for applications

  3. Active participation in the workshop and strive to solve exercises taking the help of support staff

  4. Commitment to follow on work or projects in order to apply the concepts in real life

schedule Submitted 1 year ago

Public Feedback

comment Suggest improvements to the Speaker
  • Venkatraman J
    By Venkatraman J  ~  1 year ago
    reply Reply

    Hi Abhijith,

    In terms of time you meant 480 mins for this workshop?. Can you please confirm.

  • Sarah Masud
    By Sarah Masud  ~  1 year ago
    reply Reply

    Hey Abhijith,

    I have few doubts?

    1. Can you please clarify on the time for the workshop. 480 mins is 8 hours, which will make this a full day workshop, requringus to book a decidated room for this? Also, will you be managing the whole 480 mins of the workshop by yourself. Is there a limit on number of particpants you wish to train at a given time.

    2. Can you please update the prerequisties with what softwares(like Julia) participants need to preinstall for the workshop.

    3. Have you conducted this workshop before, can you share the details with us?

    4. Will you be able to make the content of this workshop available on Github before the session begins, for audience to follow you better.

    • Abhijith Chandraprabhu
      By Abhijith Chandraprabhu  ~  1 year ago
      reply Reply

      1. Can you please clarify on the time for the workshop...

      > This will be a 8 hours workshop. We should indeed book a room for the whole day. I will have colleagues helping me out, they will be walking around and helping participants with the code or any doubts. Ideally this works well with around 30 people, but if there are more participants, we just need more teaching assistants. 

      2. Can you please update the prerequisties with what softwares(like Julia) participants need to preinstall for the workshop.

      > There is no hard requirement for the participants to install any software. We will work on juliabox.com, which is Julia hosted on the cloud and we will work using Jupyter notebooks. The only requirement is good internet and browser(hopefully not too outdated).  

      3. We have conducted this workshop in various educational institutes and in some large companies. I can email the details. 

      4. I can make the repo available to participants beforehand. 

  • Harshad Saykhedkar
    By Harshad Saykhedkar  ~  1 year ago
    reply Reply

    This is a well written proposal. All sections, especially learning outcomes are worded carefully. Keep it up!


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