heteroscedastic
commented
8 years ago @arlissc Regarding stipend and way forward is there any clarity ? I have sent you an email regarding this.
Open mozfest-bot opened 8 years ago
heteroscedastic
commented
8 years ago @arlissc Regarding stipend and way forward is there any clarity ? I have sent you an email regarding this.
[ ID ] d51b4a72-29b8-40a7-befc-564d67d6ad29
[ Submitter's Name ] Soumya Chakraborty [ Submitter's Affiliated Organisation ] Mozilla Tech Speakers / TCS [ Submitter's Twitter ] soumyaC
[ Space ] science [ Secondary Space ] youth
[ Format ] learning-lab, fireside, hands-on
Description
Machine Learning is the soul of digital disruptions across the globe, often looked as a closed door black box (probably due to potential "thought of complexity").
1) This session educates high school kids and attendees on foundations to mid advanced level of Machine Learning (ML).
2) We first learn with real life day to day examples where ML unknowingly influence human life.
3) Then we take up practical data sets, fire up small chunks of code (R || Python) to predict (forecast) something unknown.
4) The code snippets will be simple and easily understandable with people even having non programming background.
5) Attendees will be able to gain knowledge on ML, different segments of it, real life examples and how machines learn (practical programming).
6) Depth of "how to apply" depends on the audience interest and to some extent the knowledge or comfort-ability with computers and logic.
Agenda
Machine learning is sort of taboo, where generic people are interested but are afraid to get in.
1) This session breaks the shackles of those above thought concepts.
2) It guides all the attendees to the world of Machine Learning, eradicates fear, give them sense of understanding and knowledge and if interested, help them learn small real life implementations and practice it back home to improvise both the implementation and their gross learning quotient.
3) Real Life examples will contain all day to day activities in life where ML is being used so that attendees can relate themselves.
4) The code snippets provided will be generic and implementable over few other data sets for practice so that learning doesn't end after the session.
Participants
3 - () Hands on involvement () Create new models (*) Explore new areas and real life data from anyone.
15- () Hands on involvement () small gamification of models () write your own ML program (within 10 lines) () Discuss about potential pitfalls and challenges in ML
25 - () Run through slides and code demo () Explain how data sets are attacked and show real life predictions. () Write your own ML program (within 10 lines) () If interested, talk about Artificial Neural Network with a small demo.
Outcome
1) High school kids and non technical people getting interested in Machine learning and not fearing to dive in. 2) Technical people getting some more meat if they were not into ML till now and wanted to get hands dirty. Its a head start for them. They will be potential contributors to Machine learning in future. 3) The session attendees should be acting as catalyst to demystify machine learning to their friends/family/colleagues 4) Create a podium to share my knowledge even after the session to the attendees, can be slack (communication) and github (codebase) 5) For me, I will be able to curate my learning according to the session for my future technical speaking (machine learning awareness spreading) sessions.