Course Outline
Introduction to Advanced Machine Learning Models
- Overview of complex models: Random Forests, Gradient Boosting, and Neural Networks
- When to employ advanced models: Best practices and use cases
- Introduction to ensemble learning techniques
Hyperparameter Tuning and Optimization
- Grid search and random search methodologies
- Automating hyperparameter tuning with Google Colab
- Utilizing advanced optimization techniques (Bayesian optimization, Genetic Algorithms)
Neural Networks and Deep Learning
- Constructing and training deep neural networks
- Transfer learning with pre-trained models
- Optimizing deep learning models for enhanced performance
Model Deployment
- Overview of model deployment strategies
- Deploying models in cloud environments using Google Colab
- Real-time inference and batch processing capabilities
Leveraging Google Colab for Large-Scale Machine Learning
- Collaborating on machine learning projects via Colab
- Utilizing Colab for distributed training and GPU/TPU acceleration
- Integrating with cloud services for scalable model training
Model Interpretability and Explainability
- Exploring model interpretability techniques (LIME, SHAP)
- Explainable AI for deep learning models
- Addressing bias and fairness in machine learning models
Real-World Applications and Case Studies
- Applying advanced models in healthcare, finance, and e-commerce sectors
- Case studies: Successful model deployments
- Challenges and emerging trends in advanced machine learning
Summary and Next Steps
Requirements
- Solid grasp of machine learning algorithms and core concepts
- Proficiency in Python programming
- Experience working with Jupyter Notebooks or Google Colab
Target Audience
- Data scientists
- Machine learning engineers and practitioners
- AI engineers
Testimonials (3)
I really liked the end where we took the time to play around with CHAT GPT. The room was not set up the best for this- instead of one large table a couple of small ones so we could get into small groups and brainstorm would have helped
Nola - Laramie County Community College
Course - Artificial Intelligence (AI) Overview
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Artificial Neural Networks, Machine Learning, Deep Thinking
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete
