Deep Learning With Big Analytics Under A Quasi-Open Set - PowerPoint PPT Presentation

About This Presentation
Title:

Deep Learning With Big Analytics Under A Quasi-Open Set

Description:

Deep learning in Big Data analytics. The concept of deep learning is to dig a large volume of data to automatically identify patterns and extract features from complex unsupervised data without the involvement of humans, which makes it an important tool for Big Data analysis. – PowerPoint PPT presentation

Number of Views:120

less

Transcript and Presenter's Notes

Title: Deep Learning With Big Analytics Under A Quasi-Open Set


1
  • Session 1

2
  • 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.

3
  • 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.

4
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

5
  • 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.

6
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.

7
  • 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.

8
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.

9
(No Transcript)
Write a Comment
User Comments (0)
About PowerShow.com