Deep learning is a subset of machine learning that utilizes artificial neural networks for intelligent decision-making based on large datasets. It is capable of unsupervised learning and can generate features from raw data to produce various outputs, including numerical values and classifications. Applications of deep learning range from recommendation systems and autonomous vehicles to virtual assistants and genetic risk assessment.

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DeepLearningisasubsetofmachinelearningthatcreatesartificialneuralnetwork
algorithmstolearnfromlargeamountsofdatatomakeintelligentdecisions.
A QUICK INTRODUCTION TO
A QUICK INTRODUCTION TO
DEEP LEARNING
DEEP LEARNING
Machine Learning
ML algorithms are directed by the analysis
for data analysis
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Deep Learning
DL algorithms once implemented are serf-
directed for data analysis
Generated featues on its own by examing
raw data
There are more than a million data points
used for analysis
Output can be anything from a score, an
element, tect or sound etc.
Analuses a set of pre-selected relevant
features
A few thousand data points ised for analysis
The output is usually a numerical value, a
score, or a classification
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HOW DOES
DEEP LEARNING FIT IN AI?
Deep Learning is a subset of machine learning in artificial intelligence that has neural
networks capable of unsupervised learning from data.
ARTIFICIAL
INTELLIGENCE
MACHINE
LEARNING
DEEP
LEARNING
DEEP LEARNING ALGORITHMS
K-nearest Neighbours
is a simple and supervised algorithm to solve
both classification and regression problems.
Hierarchical Clustering
Groups similar objects into clusters.
Each cluster distinct from the other.
K-means Clustering
Algorithm assigns data points to categories,
or clusters, by finding the mean distance
between data points.
Artificial Neural Networks
Is a multi-layered fully connected nets.
Data are reviewed through these multiple
layers.
Recurrent Neural
Networks
Uses the output from the previous step as
the input to the next step.
Convolutional Neural
Networks
Take an input image, process it and classify it
under certain categories.
Linear Regression
Is a powerful statistical method to generate
insights on consumer behavior, under-
standing business, etc.
Logical regression
Is used when the data is linearly separable
or classifiable and the outcome is always
binary.
DEEP LEARNING
APPLICATIONS
Recommendation systems in Netflix, Amazon, and Spotify include deep learning algorithms
to enhance user experience.
Autonomous vehicles understand the realities of the road, a stop sign, or another vehicle
and decide how to do them through deep learning algorithms.
Robot advisors and Digital investment platforms use algorithms to automatically establish
portfolios and look for better investment opportunities for their clients.
Virtual assistants like Siri, Alexa, and Cortana translate your speech, book appointments and
make notes with Natural Language Processing.
Deep learning algorithms examine genetics to predict the future risk of diseases and
negative health episodes.
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