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Duration 21 hours
Course Outline
Introduction to Advanced Machine Learning Models
- Overview of complex models: Random Forests, Gradient Boosting, Neural Networks
- Application of advanced models: Best practices and specific use cases
- Introduction to ensemble learning methodologies
Hyperparameter Tuning and Optimization
- Grid search and random search methodologies
- Automating hyperparameter tuning within Google Colab
- Employing advanced optimization techniques (Bayesian, Genetic Algorithms)
Neural Networks and Deep Learning
- Construction and training of deep neural networks
- Utilizing transfer learning with pre-trained models
- Performance optimization of deep learning models
Model Deployment
- Introduction to model deployment strategies
- Deploying models in cloud environments via Google Colab
- Managing real-time inference and batch processing
Leveraging Google Colab for Large-Scale Machine Learning
- Collaborative work on machine learning projects in Colab
- Utilizing Colab for distributed training and GPU/TPU acceleration
- Integration with cloud services for scalable model training
Model Interpretability and Explainability
- Examining 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
- Case studies: Successful model deployments
- Challenges and future trends in advanced machine learning
Summary and Next Steps
Requirements
- A solid grasp of machine learning algorithms and fundamental concepts.
- Strong proficiency in Python programming.
- Prior experience with Jupyter Notebooks or Google Colab.
Target Audience
- Data scientists
- Machine learning practitioners
- AI engineers
Testimonials (2)
Getting people that never used AI some repetition in prompting and people that do use AI to consider different methods to using it.
Matthew Gay - Tarsus Pharmaceuticals
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Working from first principles in a focused way, and moving to applying case studies within the same day
