Neuroscience background

deep learning-recurrent structure

deep learning -any learning methor that can train a system with more than 2 or 3 non liear hidden layers

convolution neural network

sparse connectivity each neural only connects to part of the output of the previous layer

parameter sharing the neurons withdiffirent receptive fields can use the same set of parameters

less parameters than fully connected layer

deep learning

.deep learning

• a kind of solutions of machine learning
• types incude Arthur Samuel chess
• amazon personalization algorith
• self -driving examples
• biopsy feature (12Vs 9)

machine learning

why machine learning-recognizing patterns, recognizing anomalies, prediction

• massive parallelism, huge data volumes stoae, data distribution, highspeed networks,etc

  bigdata is every where.big data offers time advantage and data mining 

• tools for big data-bigdata techniques.

mapreduce, hadoop, locality sensitive hashing

data parallel and model parallel

• deep learning

• characterictics of big data

-volume- size and skill

velocity -geneerated at high speed

and variety, -variety like images, tables etc

veracity- uncertainty of the data

-it exceeds the processing capacity  

big data is data that exceeds the processing capacity of conventional database systems. the data is too big , moves to fast or doesnt fit the structures of your databas

• when big data is really a problem -- storage of big data, alot of things are becoming smart terminals- data from 50B devices, data centres wont fit into memory of single machine
• big data needs big models to extract understanding-(the processing arigorithims)

• tools for big data
• deep learning

challenges in big data:

1) problem with storage

More data allows us

to see new aspects, see better aspects, see different aspects

more data..more information. 

• whats big data- where does big data come from?

-examples facebook, an internet minute, smart phone users, big data is smilar to sall dat but bigger and requires diffirent approaches like techniques, tools and architctres to solve new problemms and old probles in abetter way.

it will bring challanges in volumes ,process and arigorithms 

-what is the value of big data

-helps to track adays movement/estimate adays routine 

-helps to know the emotion variations on national days

-helps with scene completion problems

• when big data is really a problem 
• tools for big data
• deep learning

data is mined so as to establish consumer emotion and trend.