Data Science is a broad term that encompasses multiple disciplines. It is a rapidly growing field of study that uses scientific methods to extract meaningful insights from given input data. The rapid growth in the field of data science has opened the eyes of researchers interested in this field to explore more into the multiple disciplines that encompass data science.
Let's see a few of these broad areas that are fundamental aspects to be covered for mastering Data science.
2. Data Science is a broad term that encompasses
multiple disciplines. It is a rapidly growing field of
study that uses scientific methods to extract
meaningful insights from given input data.
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3. The rapid growth in the field of data science
has opened the eyes of researchers
interested in this field to explore more into the
multiple disciplines that encompass data
science.
4. Let us see a few of these broad areas that are
fundamental aspects to be covered for mastering
Data science.
5. Machine Learning
The basic idea of machine learning is to allow machines
(computers) to independently learn from the wealth of data
that is fed as input into the machine. To master machine
learning, a learner needs to have an in-depth knowledge of
computer fundamentals, programming skills, data
modeling, evaluation skills, probability, and statistics.
6. Deep Learning
Deep learning is often used in data science as
it is computationally very competent
compared to traditional machine learning
methods, which require human intervention
before being machine trained.
7. Natural Language Processing (NLP)
Deep learning is often used in data science as it is
computationally very competent compared to
traditional machine learning methods, which
require human intervention before being machine
trained.
8. Statistical Data Analysis
Statistics is a branch of mathematics that includes
the collection, analysis, interpretation, and
validation of stored data. Statistical data analysis
allows the execution of statistical operations
using quantitative approaches.
9. Data mining, a major step in Knowledge
Discovery from Data (KDD), has evolved as a
prominent field in all these years as the demand
for discovering meaningful patterns from the
data has given rise to meaningful output for data
analysis.
Knowledge Discovery and Data Mining
10. Text mining is similar to text analytics and includes the
method of deriving high-quality information from text. It is
a variation of data mining that derives high- quality
information by formulating patterns and trends using
various methods such as statistical pattern learning.
Text Mining
11. Data visualization can help in identifying
outliers in data, improving the response time
of analysts to quickly identify issues,
displaying data in a concise format,
providing easier visualization of patterns,
and easy business analysis.
Data visualization
12. The various web services such as Amazon, YouTube, and
Netflix, and various e-commerce sites such as Flipkart and
Snapdeal use recommender systems to provide suggestions
to online users about new and relevant items. The items (such
as videos, music, appliances, or books) suggested are based
on the types of items being accessed by the user on a
particular website. This indirectly helps in providing a pleasant
user experience as well as the revenue generation of these
businesses increases drastically.
Recommender Systems
13. Computer vision is a field of artificial
intelligence that trains machines or
computers to understand and analyze
the visual world.
Computer vision
14. Geospatial data are structured data that includes object
information in the spatial universe. The objects can be
buildings, roads, landmarks, ecosystems, and any such
landmarks that consist of many spatial features such as
the identity of the object, its location, orientation, and
dimension. The positional coordinates of images are
represented as coordinate systems that are usually
stored in tables for reference.
Spatial Data Management
15. The future of Data Science is
undoubtedly one of the most
demanding professions today
and for years to come. Though
the recent study shows that
there are innumerable areas of
study in data science, we have
listed the fundamental areas of
study in data science in this
article.
