Keras for ML: Model Building and Cloud Deployment

Are you ready to transform your understanding of machine learning into deployable solutions? Many aspiring machine learning practitioners struggle with the crucial step of taking their trained models from development to production. This course will equip you with the foundational knowledge and practical skills to develop, train, and effectively deploy Keras-based machine learning models on cloud infrastructure, enabling you to bring your ML projects to life and make them accessible for real-world use. What you'll learn: * Understand foundational machine learning concepts and neural network architectures * Build and train deep learning models efficiently using Keras and TensorFlow * Apply data preprocessing techniques and feature engineering for model readiness * Optimize model performance and prevent common issues like overfitting * Containerize machine learning models using basic containerization principles for consistent deployment * Deploy trained Keras models to cloud environments for scalable serving * Implement basic model versioning and monitoring strategies for deployed models The course begins with foundational machine learning principles, progresses through hands-on model development with Keras, and culminates in strategies for efficient model deployment and monitoring on cloud platforms. This course is designed for absolute beginners with no prior experience in machine learning or cloud deployment. Start your journey into practical machine learning and cloud deployment today.