This course provides supplemental videos to deepen understanding of Intro to Machine Learning concepts. The learning outcomes include grasping how machine learning models work, conducting basic data exploration, building the first machine learning model, validating models, understanding underfitting and overfitting, exploring random forests, participating in machine learning competitions, and learning about AutoML. The course teaches skills such as model building, data exploration, model validation, and understanding different machine learning concepts. The teaching method involves short and engaging video lessons corresponding to each lesson on Kaggle. The intended audience for this course is individuals interested in expanding their knowledge of machine learning concepts and techniques.
Overview
Syllabus
Intro to Machine Learning Lesson 1: How Models Work | Kaggle.
Intro to Machine Learning Lesson 2: Basic Data Exploration | Kaggle.
Intro to Machine Learning Lesson 3: Your First Machine Learning Model | Kaggle.
Intro to Machine Learning Lesson 4: Model Validation | Kaggle.
Intro to Machine Learning Lesson 5: Underfitting and Overfitting | Kaggle.
Intro to Machine Learning Lesson 6: Random Forests | Kaggle.
Intro to Machine Learning Lesson 7: Machine Learning Competitions | Kaggle.
Intro to Machine Learning Bonus Lesson: AutoML | Kaggle.
Taught by
Kaggle
