Deep learning is a subset of machine learning based on artificial neural networks (ANN), where interconnected nodes, or neurons, learn from input data. There are various types of neural networks, including feedforward, recurrent, and convolutional, each suited for different applications such as pattern recognition, natural language processing, and object recognition. Key applications of deep learning include healthcare, financial fraud detection, autonomous vehicles, and smart agriculture.

2. Deep learning is
the branch of
Machine Learning
which is based on
Artificial Neural
Network (ANN)
architecture.

3. DEEP LEARNING

5. An Artificial
Neural Network or
ANN uses layers
of interconnected
nodes called
neurons that work
together to
process and learn
from the input
data.

7. TYPES OF NEURAL NETWORKS
FEEDFORWARD NEURAL
NETWORKS:- UESD TO
PERFORM BASIC PATTERN AND
IMAGE RECOGNITION.
RECURRENT NEURAL
NETWORKS:- USED IN NATURAL
LANGUAGE PROCESSING AND
SPEECH RECOGNITION.
CONVOLUTIONAL NEURAL
NETWORKS:- USED IN OBJECT
RECOGNITION AND VIDEO
ANALYSIS.

12. Applications of Deep Learning
1. Healthcare
2. Financial Fraud Detectio
n
3. Natural Language Proces
sing
4. Autonomous Vehicles

13. HEALTHCARE

14. FRAUD DETECTION

15. NATURAL LANGUAGE PROCESSING

16. AUTONOMUS VEHICLE

17. SMART AGRICULTURE

18. SPACE
TRAVEL

22. THANK
YOU