Global Certificate in Model Evaluation: A Practical Approach

The course covers various techniques for evaluating machine learning models, including cross-validation, bias-variance tradeoff, and overfitting. It also delves into advanced topics such as ROC curves, lift charts, and Gain charts. Learners will gain hands-on experience in model evaluation using popular tools and libraries such as Scikit-learn, TensorFlow, and Keras. Upon completion, learners will be able to evaluate machine learning models effectively, ensuring the accuracy and reliability of predictive models. This skill is in high demand across industries, making this course an excellent choice for professionals looking to advance their careers in data science, machine learning, or artificial intelligence.