· Current achievements of Machine learning
· Types of learning: supervised and unsupervised
· Algorithm overview and model selection
· Data management
· Metrics
· Converting business problems to ML language
· Methodology
· Key points
· Common failures
· Deploying ML to production
· Classification tasks
· Regression tasks
· Personalization tasks
· Text tasks
· Using ML to improve customer experience
· Working out a real-world problem throughout developments steps, from design, collecting data, early versions, production, and optimizations
· Summary including Q&A