These Programming Language courses cover a broad spectrum of topics, ensuring you stay current with industry standards and best practices.
Getting more advanced topics in C language that are more suitable for programming the embedded systems.
Move beyond basic scripts and build real-world automation tools for your domain environment.
Go beyond grid search to tune complex machine learning models with sequential model-based optimization.
Go beyond default settings with robust tuning, cross-validation, and performance metrics for better performing machine learning models.
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Build dynamic, efficient, and framework-agnostic machine learning pipelines using the Define-by-Run API.
Cut training costs and accelerate model tuning with advanced search strategies.
Interpret any model with visual tools like permutation feature importance, partial dependence plots, accumulated local effects and individual conditional expectation
Master global and local explainability for decision trees, random forests, and gradient boosting machines.
Explain what drives your model and each prediction using regression coefficients, odds ratios and feature importance
Understand SHAP values in depth to explain machine learning models accurately, critically and with confidence.
