Personal Information
Organización/Lugar de trabajo
Pune Area, India India
Ocupación
Data Analyst at Gurucul Solutions
Sector
Technology / Software / Internet
Acerca de
Diving into Data Science and Machine Learning with Big Data.......
5 Days effort, 40 GB RAM(REDHAT,Linux,5 Nodes Hadoop cluster on Openstack),500 GB HDD,20 GB retail data for buyers,2 Hive Joins(2.5 Hours run),Data conditioning,Normalization,SVMwithSGD(Support Vector Machine using Stochastic Gradient Descent.) with Spark MLIB,Distributed computation,20 Iterations for model building(1.5 Hours run),auROC: Double = 0.7858184517425998, Accuracy to predict repeat buyer is 78.58147387964868 %
Yeeeppeeeeeeeeeeeeeeeee!!!
P.S: Model is in scala so any scala or Java API can call it to get the prediction.
- Presentaciones
- Documentos
- Infografías
Notes from Coursera Deep Learning courses by Andrew Ng
Tess Ferrandez
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Hace 6 años
Study of End to End memory networks
ASHISH MENKUDALE
•
Hace 7 años
Deep Learning for Chatbot (4/4)
Jaemin Cho
•
Hace 6 años
Hive on spark is blazing fast or is it final
Hortonworks
•
Hace 9 años
2016 Spark Summit East Keynote: Matei Zaharia
Databricks
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Hace 8 años
Piotr Mirowski - Review Autoencoders (Deep Learning) - CIUUK14
Daniel Lewis
•
Hace 9 años
Sparkling Water Webinar October 29th, 2014
Sri Ambati
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Hace 9 años
How to win data science competitions with Deep Learning
Sri Ambati
•
Hace 9 años
10 Lessons Learned from Building Machine Learning Systems
Xavier Amatriain
•
Hace 9 años
Anomaly Detection
DataminingTools Inc
•
Hace 14 años
Lessons From Hermione About Presentations
vmerege
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Hace 9 años