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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.
Beginner-friendly introduction to machine learning for non-engineers. Learn core concepts, data types, algorithms, and practical applications. Develop skills to translate real-world challenges into ML solutions using accessible tools.
Empowering young people, especially women, to pursue machine learning careers through hands-on experience, data exploration, model training, and ethical considerations.
Explore key predictive analytics techniques including regression, decision trees, ensembles, and neural networks. Gain hands-on experience in model fitting, performance evaluation, and practical application of machine learning methods.
Learn to train Object Detection Transformers using DETR, from environment setup to custom dataset training and model evaluation. Covers PyTorch, COCO datasets, and PyTorch Lightning for efficient deep learning workflows.
Learn essential machine learning concepts and techniques for coders, covering fundamental principles and practical applications across 12 comprehensive lessons.
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.
This course will walk you through creating a machine learning prediction solution with Python, the Scikit-learn library, and the Jupyter Notebook environment.
Get an introduction to the concepts and mechanics of machine learning with Azure.
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.
Turn predictive analytics into a profit center at your organization. Learn how to measure the return on investment (ROI) and prove the long-term value of your projects.
Explore machine learning in finance: data analysis, supervised/unsupervised learning, NLP, time series forecasting. Gain practical skills for banking innovation and ethical AI implementation.
R is the key that opens the door between the problems you want to solve with data and the answers you need. This course walks you through the process of answering questions through data.
This mid-level course takes you through how to create one of the most common types of machine learning: supervised learning models.
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