Mastering Machining AI: From Knowledge to Creation of Powerful ML Models

Learning outcomes

1. The learner demonstrates proficiency in using a specific framework to prepare the data provided for the creation of machine learning models. They effectively apply data visualization techniques to gain insight into the dataset and preprocess the data through various processing methods, ensuring their suitability for model training. They also employ feature selection and extraction techniques to identify and extract relevant features for creating the machine learning predictive model. Additionally, they establish appropriate storage mechanisms for the processed data and extracted features after completing this lesson.
2. The learner successfully creates a predictive AI model by training it on the prepared feature sets. They accurately follow the instructions provided on the learning path to build and train the machine learning model using the selected features. They apply appropriate techniques to evaluate and test the model's performance on a separate set of features, assessing its predictive capabilities after completing this lesson.
3. The learner effectively implements the trained machine learning predictive model under real-like conditions. They deploy the model and use it to make predictions or classifications in practical scenarios. They critically evaluate the results generated by the model and assess its overall effectiveness, considering factors such as accuracy, robustness, and suitability for the intended application. They provide insightful judgments and recommendations based on their evaluation after completing this lesson.