Abhijith Chandraprabhu
Data Scientist
Julia Computing
location_on India
Member since 5 years
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Abhijith Chandraprabhu
Specialises In
I have around 4 years of experience in Data Science. Currently I am working at Julia Computing as a Data Scientist. My thesis work involved building a scalable machine learning algorithm for recommender systems. The system outperforms the winning algorithms of NETFLIX competition. I have also worked at Gramener for a year and have some decent experience with visual data analysis. I also teach at MSRIT as a visiting faculty.
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Computational Machine Learning
Viral B. ShahCo-inventor of JuliaJulia Computing Inc.
Abhijith ChandraprabhuData ScientistJulia Computingschedule 1 year ago
480 Mins
Workshop
Intermediate
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:
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Learn machine learning, deep learning and AI concepts
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Provide hands-on training so that students can write applications in AI
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Provide ability to run real machine learning production examples
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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.
-
-
keyboard_arrow_down
Computational Machine Learning
480 Mins
Workshop
Intermediate
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:
-
Learn machine learning, deep learning and AI concepts
-
Provide hands-on training so that students can write applications in AI
-
Provide ability to run real machine learning production examples
-
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.
-
-
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