Deep Learning about| IABAC Certification

Deep learning is a branch of AI that employs neural networks to detect patterns in data. It drives image recognition, speech processing, and autonomous systems. Its vast databases and computational capacity enable innovations in healthcare, finance, robotics, and natural language processing.

1. iabac.org
DEEP
LEARNING

2. WHAT IS DEEP
LEARNING?
A branch of machine learning influenced by
the human brain.
Utilizes artificial neural networks to analyze
and learn from data.
Helps solve complex problems such as
image and speech recognition.
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3. iabac.org
WHY IS DEEP LEARNING
IMPORTANT?
powers current AI applications.
Helps with automation and decision-
making.
Used in fields such as healthcare, finance,
and self-driving vehicles.

4. iabac.org
HOW DEEP LEARNING
WORKS
Uses layers of artificial neurons to organize
data.
Discovers patterns and relationships in
data.
Increases accuracy with further training and
data.

5. KEY COMPONENTS OF
DEEP LEARNING
Neural Networks: The Foundation of Deep
Learning.
Activation Functions: Help the network to
learn difficult patterns.
Optimization Algorithms: Improve
Learning and Accuracy.
Loss Function: Evaluate how effectively the
model performs.
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6. POPULAR DEEP LEARNING
ARCHITECTURES
Convolutional Neural Networks (CNNs): Used for
image processing.
Recurrent Neural Networks (RNNs): Used for
sequential data such as text and speech.
Generative Adversarial Networks (GANs): Develop
new content such as photos and music.
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7. iabac.org
TOOLS AND FRAMEWORKS
FOR DEEP LEARNING
TensorFlow - Google's deep learning framework.
PyTorch - Facebook's framework for research and
production.
Keras - A user-friendly API for creating models
Scikit-learn - Useful for machine learning tasks.

8. REAL-WORLD APPLICATIONS
OF DEEP LEARNING
Self-driving vehicles (Tesla and Waymo).
Virtual assistants (Alexa, Siri, Google Assistant) .
Healthcare diagnostics (AI-assisted disease
detection).
Detecting fraud in banking.
language translation (Google Translate).
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9. FUTURE OF DEEP LEARNING
Continuous progress in AI technology.
More efficient and explainable models.
AI will affect more industries.
Ethical Considerations for AI Development.
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10. Visit: iabac.org
THANK YOU!