The document provides an overview of deep learning, highlighting its differences from machine learning, operational mechanisms such as forward and backpropagation, and the increasing career opportunities in this field, which offer competitive salaries. It further explains the growing demand for deep learning due to its accuracy and efficiency, along with the challenges it faces, like data requirements and regulatory concerns. Contact details for further inquiries are also included.

1. WHAT IS DEEP LEARNING?
PHONE NO : 9212172602
Email id : query@cetpainfotech.com
www.cetpainfotech.com

2. OVERVIEW
 Deep Leaning VS Machine Learning
 How deep learning works?
 Career Opportunities in Deep Learning
 Why Deep Learning is Growing?
 Challenges with Deep Learning
 Contacts

3. DEEP LEANING VS MACHINE LEARNING
 If deep learning is a subset of machine learning,
how do they differ? Deep learning distinguishes
itself from classical machine learning by the type
of data that it works with and the methods in
which it learns.
 Machine learning algorithms leverage structured,
labeled data to make predictions—meaning that
specific features are defined from the input data
for the model and organized into tables. This
doesn’t necessarily mean that it doesn’t use
unstructured data; it just means that if it does, it
generally goes through some pre-processing to
organize it into a structured format.

4. HOW DEEP LEARNING WORKS?
Deep learning neural networks, or artificial neural networks,
attempts to mimic the human brain through a combination of data
inputs, weights, and bias. These elements work together to
accurately recognize, classify, and describe objects within the data.
Deep neural networks consist of multiple layers of interconnected
nodes, each building upon the previous layer to refine and
optimize the prediction or categorization. This progression of
computations through the network is called forward propagation.
The input and output layers of a deep neural network are
called visible layers. The input layer is where the deep learning
model ingests the data for processing, and the output layer is
where the final prediction or classification is made.
Another process called backpropagation uses algorithms,
like gradient descent, to calculate errors in predictions and then
adjusts the weights and biases of the function by moving
backwards through the layers in an effort to train the model.
Together, forward propagation and backpropagation allow a neural
network to make predictions and correct for any errors
accordingly. Over time, the algorithm becomes gradually more
accurate.

5. CAREER OPPORTUNITIES IN DEEP LEARNING
Deep learning is a popular term in the computer field. A
career in Artificial intelligence, machine learning, and
deep learning are booming nowadays. Enormous job
opportunities are getting created every day for these
fields but demand for deep learning is high for sure, as
per the reports.
For deep learning professionals, the average salary
range in the US is approximately $70,000 to $75,000/year.
There is a high demand for careers in deep learning and
AI as many jobs are available for this field with a good
salary. As a result, most of the professionals are trying
to get trained in deep learning.

6. WHY DEEP LEARNING IS GROWING?
•Deep learning now provides more accurate
responses than humans, and as a result, this
technology is rapidly spreading around the
world. The ability to perform tasks without
human intervention is the driving force
behind the deep learning market growth.
•Explosions of features and datasets.
•Focus on customization and real time
decisioning .
•Higher operational efficiency.
•Ensure consistent customer experience and
regulatory compliance ……

7. CHALLENGES WITH DEEP LEARNING
 Works better with large
amount of data.
 Some models are very hard to
train , my take weeks or
months.
 Overfitting
 Black box and hence may have
regulatory challenges ,
particularly for BFSI.

8. CONTACT US
PHONE NO : 9212172602
Email id : query@cetpainfotech.com
Website : https://www.cetpainfotech.com/
THANK YOU!!!!