Deep Learning With Big Analytics Under A Quasi-Open Set

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• Session 1

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• The present and the future are completely driven
  by technology. You can find a number of changes
  that are taking place around us, and one of the
  developments that we have seen is big data. But
  before heading to understand this, it's important
  to know that data is the key driver of change for
  different industries. You can find a number of
  companies investing in optimally using data, and
  one such technology that we are using at its best
  is big data. It has been one of the most
  revolutionary technologies of the present, which
  is going to pave the way for a strong future.

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• The big future for big data awaits us, and it is
  taking place at a breakneck pace. The big data
  market is expected to grow with a CAGR of 53.7
  during the period of 2015- 2022. The market size
  of big data is expected to reach 100 billion by
  the end of this year. Well, when we are talking
  about the growth of big data analytics
  certification, then it's not just the use of this
  technology which is transforming the world,
  rather it is also paving the way for a lot of
  development of other technologies like machine
  learning, AI and deep learning. It would not be
  wrong to claim here that big data is also paving
  the way for a new set of job opportunities. It
  has led to the rise in the demand for data
  analytics certification programs.

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Let's shift our focus back to deep learning with
big data analytics and how it is developing under
the quasi-open set

• Well, if you are from the field of technology,
  then you would be aware of the concept of big
  data and deep learning. Now let's have a look at
  how these two are impacting each other.
• Deep learning is a subset of machine learning.
  And these technologies work on data. The data is
  the key driver, and with the help of the right
  kind of algorithm, the data is interpreted, and
  conclusions are drawn to enable the machines to
  perform a task. When it comes to deep learning,
  then it finds its use cases across different
  segments like

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• Healthcare
• Manufacturing
• Finance
• All these segments rely on data for the vast
  majority of their work. With the help of deep
  learning, we can expect the system to work
  flawlessly, which eventually makes it more
  efficient.
• Here it becomes important to mention about the
  neural network that is one of the key algorithms
  working behind the scene of deep learning. Neural
  networks are designed to work like the human
  brain. They can analyze the data similar to that
  of a human brain and process it so that the
  machine can make a decision and perform
  accordingly.

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Providing quasi-open set to analyze the working
of big data

• Now shifting our focus on the quasi-open set,
  then here we try to create an environment where
  big data performs under this system, which is
  created by the developers.
• Usually, the big data classification models work
  under a semi-supervised learning framework. This
  is the primary because of the available unlabeled
  sample and high cost to collect the labeled
  sample. Hence, it assumed that the unlabeled
  samples that we have are from both the same and
  different classes that are there in the labeled
  training samples, which is also called here as a
  quasi-open set. In simple words, the quasi-open
  set has samples from source classes, which are
  indicated by labeled and unlabelled training
  samples and from novel classes.

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• What we can conclude here is that end-to-end
  learning is considered to be the most pliable
  solution for big data analytics only if models
  are trained to classify source classes and novel
  classes.
• Well, this was one of the tests performed by
  developers to ensure that how does big data and
  deep learning work in this kind of environment.
  Big data experts continuously work in newer kinds
  of environments to check how the machine performs
  and what can enhance its efficacy without any
  flaw. The aim is to create a system that is
  flawless and performs just like a human.

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Conclusion

• In the times to come, we are going to see some
  great changes, and one of them is surely going to
  be a surge in the field of technology, and big
  data is one of them. It is paving the way for a
  lot of development, inclusive of the demand for
  big data certification and data analytics
  certification. If you are looking forward to
  making your career grow, then this is the area
  where you should be investing as a big data
  expert. You are required to continuously check
  the performance of the system, under different
  environments like the one we have mentioned
  above. With the right knowledge, you can excel as
  a big data expert, and Global Tech Council is
  here to provide you the same. The data analytics
  certification is a comprehensive course
  containing all this information along with
  practical implications of the same. So, if you
  wish to see your career boom, you must invest in
  learning big data and data analytics.

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