Applied Deep Learning with Keras

🎓 Course Title: Applied Deep Learning with Keras

Course Headline:

Solve complex real-life problems with the simplicity of Keras

Course Description:

Embark on a journey to master the art of designing neural networks that can tackle complex machine learning challenges. "Applied Deep Learning with Keras" is meticulously crafted to guide you from the basics of machine learning and Python programming, all the way through to the intricacies of applying Keras for developing efficient deep learning solutions.

This course isn't just about theoretical knowledge; it's about practical application. You will:

• Understand the Basics: Start with the fundamentals of machine learning and Python to ensure a solid foundation for your deep learning journey.
• Explore Keras Models: Dive into the core of Keras, exploring its various models, and learn how to build prediction models for real-world problems such as disease prediction and customer churn analysis.
• Model Evaluation: Master the art of evaluating your models by cross-validating them using Keras Wrapper and scikit-learn, ensuring that you're on the path to creating the most accurate predictors.
• Optimization Techniques: Discover how to apply L1, L2, and dropout regularization techniques to improve model accuracy and maintain performance through precise model tuning using null accuracy, precision, and AUC-ROC score methods.
• Real-World Application: By the course's end, you will have acquired the skills necessary to use Keras for building high-level deep neural networks applicable to a myriad of real-world scenarios.

About the Authors:

• Ritesh Bhagwat holds a master’s degree in applied mathematics with a specialization in computer science and boasts over 14 years of experience in data-driven technologies. His expertise spans from data warehousing and business intelligence to machine learning and artificial intelligence, with a keen interest in Bayesian statistics.

• Mahla Abdolahnejad is a Ph.D. candidate in systems and computer engineering at Carleton University, Canada. Her research focuses on deep unsupervised learning for computer vision applications, with an aim to understand how machines can learn visually similar to humans.

• Matthew Moocarme is a director and senior data scientist at Viacom’s Advertising Science team. His work involves designing data-driven solutions to unlock insights, streamline processes, and solve complex problems using advanced data science techniques. A classically-trained physicist with a Ph.D., Matthew combines his expertise in deep learning and music theory to innovate in the field of AI.

Join us on this comprehensive course and transform your approach to machine learning by leveraging the power of Keras for real-world applications. Let's turn your passion for data into actionable deep learning solutions! 🤖💡

Enroll Now to:

• Unlock a New World: Discover the potential of neural networks and deep learning in solving complex problems.
• Gain Expert Knowledge: Learn from industry experts who bring practical experience into the classroom.
• Join a Community: Connect with peers and professionals alike, sharing a common interest in deep learning and its applications.

Ready to dive into the world of Deep Learning with Keras? Click here to start your journey today! 🌊🚀