Engineering and Technology
Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.
Machine learning is a rapidly growing field that focuses on teaching machines and computers to learn from existing data in order to make accurate predictions on new data. This course offers a comprehensive introduction to supervised learning, a fundamental aspect of machine learning, using the Python programming language. Through this course, participants will gain the necessary skills to construct predictive models, optimize their parameters, and evaluate their performance on unseen data. Real-world datasets will be utilized throughout the course to provide practical experience. Participants will also have the opportunity to work with scikit-learn, a widely used and intuitive machine learning library for Python.
by DataCamp
Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.
by DataCamp
Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this inter...
by DataCamp
Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using...
by DataCamp
Sharpen your knowledge and prepare for your next interview by practicing Python machine learning int...
by DataCamp
Learn to tune hyperparameters in Python.
by DataCamp
Learn how to use Python to analyze customer churn and build a model to predict it.
by DataCamp
Explore the concepts and applications of linear models with python and build models to describe, pre...
by DataCamp
Learn to process, transform, and manipulate images at your will.
by DataCamp
This course teaches the big ideas in machine learning like how to build and evaluate predictive mode...
by DataCamp
Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression...