GDG MLCC STUDY JAM | 28-7-2018

Machine Learning Crash Course

  1. Machine Learning Crash Course (MLCC) Study Jam aims to raise the technical proficiency of the participants in the field of Artificial Intelligence.
  2. The event scheduled from 4pm to 6:30pm.
  3. MLCC Study Jam comprised of 70% students and 30% developers, 20% women attendees from 4 different companies.
  4. 90% of attendees rated the event 4+ out of 5.

 

EVENT OVERVIEW

  • Participants were able to understand the concepts Features, Regression, Training and Loss in Machine Learning.
  • Installation and Configuration of Anaconda.
  • At the end of the event, participants were able to train the machine using Anaconda.

 

IMPACT

# Participants:           23

# Speakers:                 2

# Women attendees:          7

# Machine training:   1

 

AGENDA

MACHINE LEARNING CRASH COURSE (MLCC) STUDY JAM

Location:      Arunachala Arcade, Pasumalai Arch, Madurai

Date:              28-07-2018

Time:             4:00PM – 6:30PM

 

TIMINGS ACTIVITIES SPEAKERS
4:00PM – 4:30PM Registration
4:30PM – 5:00PM What is Machine Learning? Mr. Sairam
5:00PM – 5:30PM MLCC Session Mr. Ram Kumar
5:30PM – 5:45PM Introduction to Anaconda Mr. Ram Kumar
5:45PM – 6:15PM ML Training using Spyder Mr. Ram Kumar
6:15PM – 6:30PM Networking and Feedback

 

PHOTOS

What is Machine Learning by Mr. Sairam

ramkumarmlcc

MLCC Session by Mr. Ram Kumar

 

 

FEEDBACK

  • We have received positive comments and suggestions for improvements from the participants which will be used to improve the further workshop.

 

LESSONS LEARNT

  • Based on feedback, we make sure that the sessions are still more engaging and interactive with more hands-on activities and sessions.

 

NEXT STEP

  • We would like to run more parallel hands on session in relation to Machine Learning Study Jam.

 

THANK YOU

We would like to convey our sincere regards and thankfulness to the attendees for attending the workshop.

Leave a Reply

Your email address will not be published. Required fields are marked *