Distinguishing Between Artificial Intelligence and Data Science Using Images

Artificial Intelligence & Data Science

AI, ML and Deep Learning in a Euler Diagram



Development of a smart computer system that is able to perform task that normally requires human intelligence such as Visual Perceptions, Speech Recognition, Decision Making & Language Translations

Development of a ‘Computer Program or Machine’ which can Learn, Think and Act on its own

Learn : Acquire Data 
Think : Analysis Of Data 
Act :  Taking Action

A broad view of Data Science

Data Science Venn Diagram




Machine Learning ( ML ) : Applying statistics on computer 

Traditional Software ( TS ) : Doing Business using computer

Traditional Research ( TR ) : Use of statistics to understand , explain and grow business

Data Science ( DS ): A Broad canvas that encompasses Machine Learning, Traditional Software & Traditional Research
 
Machine Learning

# A Discipline under Data Science

# Imparts and Empowers Machine to  Learn , Think  , Act  for themselves

# Help’s computers to learn from pattern’s & behavior and act accordingly without any human intervention or being explicitly programmed

ML Technology -

It uses Algorithms & Mathematical Models to analyze data and learn from it. For Ex - Following statistical models are used to analyze data

# Linear Regression

# Decision Trees

# Naïve Bayes’ Classification Model

Exploratory Data Analysis -

# This is the first step in machine learning to be apply on data set

# It deal with doing Descriptive and Inferential statistics on data set

Data Science

# It is root of all

# A discipline that utilize a combination of Mathematical , Statistical and Computational tools to acquire , process and analyze Big Data .

# It help in impart meaning  from large amount of Big Data

Data Scientist and Analyst uses –

# ‘Statistical Inference’ to extract hidden & useful patterns from large data sets

# And ‘Data Visualization’ techniques to communicate those insights into business oriented directions ( With Domain Expertise )

Processes used in Data Science -

# Data Extraction
# Data Cleaning
# Data Analysis
# Visualization of Data
# Generalization of actionable insights