2. • Data science?
• Introduction to R
• Data analysis?
• Data visualization?
• Predictive Analysis
• Deep learning?
•
3. WHAT IS DATA SCIENCE?
• Data science is a broad field that refers to the collective
processes, theories, concepts, tools and technologies
that enable the review, analysis and extraction of
valuable knowledge and information from raw data. It is
geared toward helping individuals and organizations
make better decisions from stored, consumed and
managed data
4. INTRODUCTION TO R
• R is a programming language and software environment for
statistical computing and graphics that is supported by the R
Foundation for Statistical Computing. The R language is widely used
among statisticians and data miners for developing statistical
software and data analysis.
• R language is an open source program maintained by the R core-
development team. It is a team of volunteer developers from across
the globe.
• R language used for performing statistical operations
• It is available from the R-Project website www.r-project.org.
• R is a command line driven program.
• The user enters commands at the prompt (> by default) and each
command is executed one at a time.
5. WHAT IS DATA ANALYSIS?
• Data analysis is a process of inspecting, cleansing,
transforming, and modeling data with the goal of
discovering useful information, informing conclusions,
and supporting decision-making.
• This is the step where the cleaned and aggregated data
is imported into analysis tools. These tools allow you to
explore the data, find patterns in it, and ask and answer
what-if questions. This is the process by which sense is
made of data gathered in research by proper application
of statistical methods
6. WHAT IS DATA VISUALIZATION?
• Data visualization is a general term that describes any
effort to help people understand the significance of data
by placing it in a visual context. Patterns, trends and
correlations that might go undetected in text-based data
can be exposed and recognized easier with data
visualization software
7. WHAT IS PREDICTIVE ANALYSIS?
• Predictive analytics is a form of advanced analytics that
uses both new and historical data to forecast activity,
behavior and trends. It involves applying statistical
analysis techniques, analytical queries and
automated machine learning algorithms to data sets to
create predictive models that place a numerical value --
or score -- on the likelihood of a particular event
happening.
8. WHAT IS DEEP LEARNING?
• Deep learning is a collection of algorithms used in machine
learning, used to model high-level abstractions in data
through the use of model architectures, which are composed
of multiple nonlinear transformations. It is part of a broad
family of methods used for machine learning that are based
on learning representations of data.
• Deep learning is a specific approach used for building and
training neural networks, which are considered highly
promising decision-making nodes. An algorithm is considered
to be deep if the input data is passed through a series of
nonlinearities or nonlinear transformations before it becomes
output..
