Making Machine Learning Accessible Using Keras

Overview

Join us to unravel the potential of Keras, the user-friendly deep learning API, designed to make artificial intelligence more accessible. This event focuses on utilizing Keras for solving complex business problems with ease.

Key Highlights Include:

• Understanding the core features of Keras
• Exploring various APIs for effective AI model development
• Step-by-step guide to building models
• Integrating Keras seamlessly with TensorFlow

Whether you're a seasoned expert or just starting, this session will enhance your ability to harness AI technologies effectively.

Syllabus

• Introduction to Machine Learning and Keras
Overview of Machine Learning
Introduction to Keras and its role in the AI ecosystem
Benefits of using Keras for business applications
• Setting Up Your Environment
Installing Keras and TensorFlow
Basic configuration and setup
Introduction to Jupyter Notebooks and Python
• Understanding Keras APIs
Sequential API
Functional API
Model Subclassing
• Building and Training Models
Defining models using Sequential API
Implementing models using Functional API
Customizing models with model subclassing
Compiling, training, and evaluating models
• Handling Data with Keras
Preprocessing and preparing data
Using Keras Datasets
Data augmentation for improving model performance
• Advanced Features in Keras
Custom layers and activations
Callbacks and custom training logic
Transfer learning with Keras
• Integrating Keras with TensorFlow
Leveraging TensorFlow features in Keras
Model deployments using TensorFlow Serving
Using TensorFlow Lite for mobile and edge devices
• Real-world Applications and Case Studies
Solving business problems with Keras
Industry-specific use cases
Building AI solutions for practical business scenarios
• Best Practices and Model Performance
Model optimization and tuning
Strategies for avoiding overfitting
Experiment tracking and version control
• Conclusion and Future of Keras
Recap of key learnings
Current trends and future directions in Keras
Resources for further learning and development in AI
• Course Project
Building a complete machine learning project using Keras
Presentations and feedback sessions

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Subjects

Conference Talks