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           Big Data refers to increasingly larger, more diverse, and more complex data sets that challenge the abilities of traditionally or most commonly used approaches to access, manage, and analyze data effectively.  As we are entering an age of Big Data. Big Data give both unique opportunities and amazing challenges.  Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data.


            Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can contain useful information about problems such as national intelligence, cyber security, fraud detection, marketing, and medical informatics. Key benefit of Deep Learning is the analysis and learning of massive amounts of unsupervised data, making it a valuable tool for Big Data Analytics where raw data is largely unlabeled and un-categorized. This course provides introduction to big data tools and deep learning frameworks.

Introduction to Bigdata and Deep Learning  for HPC

Introduction to Deep Learning

Introduction to Linux and Python

Introduction to CAFFE A Deep Learning Framework

Deep learning using Caffe Basic Structure

Deep learning using Caffe Network Layers

Deep learning using Caffe Execution Process



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UCERD: Unal Center of Education Research and Development
 

Introduction to Bigdata and Deep Learning for HPC