Learn to build powerful models in this Machine Learning Nanodegree with PyTorch. Master supervised, unsupervised, and deep learning techniques through projects involving customer segmentation and image classification.
Welcome to Machine learning with Pytorch
From theory to application, this course guides you through supervised learning essentials. Learn to select, implement, and refine models that solve complex classification and regression tasks.
Learn the fundamentals of neural networks with Python and PyTorch, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classify new images.
Learn to apply unsupervised learning methods like K-means and Gaussian mixtures to extract value from raw data. Develop skills in feature extraction and cluster validation to enhance data analysis.
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Multivariable calculus. Data wrangling. Python for data science. Basic supervised machine learning. Intermediate Python. Linear algebra. Basic descriptive statistics. Basic calculus. Basic probability
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