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Specialized CrewAI Agent Workflows: Task-Centric Tooling | View in the Skills Network Catalog

Build specialized AI Agent workflows with task-centric tooling using CrewAI. Apply in-demand skills to solve real-world challenges with AI, leveraging LLMs. Create and orchestrate AI agents, work with databases, and refine prompt engineering for a customer service chatbot used by a restaurant. This hands-on project is a necessity for all software engineers and machine learning engineers seeking to level-up their skills and it takes only 30 minutes!

Evaluating an NBA Player's Team Impact via Regression | View in the Skills Network Catalog

Learn how to apply Random Forest and Kernel Ridge Regression by analyzing an NBA player's real game performance. In this guided project, you’ll engineer features, tune model hyperparameters, and analyze feature importance to understand what truly drives a player’s performance on the court. You'll leverage pandas for data manipulation, scikit-learn for model training and evaluation, and matplotlib for visualization. By the end, you’ll be able to confidently build, configure, and interpret industry standard regression models for a wide range of analytical use cases.

Learn Interpretable ML with Graph Visualizations | View in the Skills Network Catalog

Your model interpretation is probably wrong. Partial Dependence Plots create impossible scenarios when features correlate, leading to false insights and bad decisions. ALE plots solve this fundamental problem. Learn the theory, build them yourself with scikit-learn, and finally get model explanations you can trust.