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AI is a bigger picture and machine learning and deep learning are its sub parts. AI, machine learning and deep
learning are the subset of each other. Deep Learning is the next evolution of machine learning.
In order to understand the difference between the two let us take help of the table given below.
Parameters Deep Learning Machine Learning
When the size of the data is small, Machine Learning algorithm can easily work
a deep learning algorithm does not with smaller data set.
Data Dependency perform well as a deep learning
algorithm needs large amounts of
data to understand perfectly.
Deep Learning algorithms are heavily Machine Learning algorithms can work on
Hardware Dependency
dependent on high-end machines. low end machines as well.
Deep Learning algorithm solves the When we are solving a problem using a
problem end to end. traditional machine learning algorithm it is
Problem Solving generally recommended that we first break
Approach down the problem into different sub parts
and solve them individually and then finally
combine them to get the desired result.
Usually, Deep Learning algorithms Machine Learning algorithms take much less
take a long time to train because time to train.
Execution Time
there are many parameters making
the training time longer than usual.
Domains of AI
Based on the data given to AI system, it can be classified into 3 domains: Data Science, Computer Vision (CV)
and Natural Language Processing (NLP). Let us learn about them in detail.
Data Science
Data Science is the domain of artificial intelligence that processes the given data to find solutions or predict
the outcomes for a problem statement. The type of data that can be used is numeric and alphanumeric. It deals
with data systems and processes, in which the system collects numerous data, maintains data sets and derives
meaning/sense out of them. The information extracted through data can be used to make a decision about it.
130 Touchpad Artificial Intelligence-X

