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Learn Model Evaluation, earn certificates with free online courses from Stanford, Johns Hopkins, UC San Diego, Duke and other top universities around the world. Read reviews to decide if a class is right for you.
Accelerated introduction to NLP, covering machine learning basics, text preprocessing, vectorization, and advanced neural network architectures like RNNs, LSTMs, and Transformers.
Explore machine learning and computer vision fundamentals, advanced neural network architectures, and applications in object detection and semantic segmentation.
Learn machine learning techniques for tabular data, including model evaluation, feature engineering, tree-based models, hyperparameter tuning, and neural networks using AWS SageMaker.
In this course you'll learn to add multiple variables to linear models and to use logistic regression for classification.
This course is designed to get you up to speed with the most important and powerful methodologies in statistics.
Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.
Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.
In this course you'll learn how to apply machine learning in the HR domain.
This course will walk you through creating a machine learning prediction solution with Python, the Scikit-learn library, and the Jupyter Notebook environment.
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.
Get an introduction to the concepts and mechanics of machine learning with Azure.
In this course, you'll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.
Prepare for your upcoming machine learning interview by working through these practice questions that span across important topics in machine learning.
Machine learning is exciting, yet, it may sound more complicated than it is actually is. This course empowers you with the necessary theory and practice to become confident about how machine learning works by building a hands-on solution.
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