Offered By: IBMSkillsNetwork
Classification with PyTorch
Designed for students and enthusiasts, this course equips you with the knowledge and practical skills to build powerful and accurate classification models using PyTorch. It offers a hands-on learning experience, allowing you to apply your knowledge through coding exercises and lessons so by the end of the course, you will possess the skills to build, train, and evaluate classification models using PyTorch. "Classification with PyTorch" is a part of a PyTorch Learning Path, check Prerequisites.
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Artificial Intelligence
374 EnrolledAt a Glance
Designed for students and enthusiasts, this course equips you with the knowledge and practical skills to build powerful and accurate classification models using PyTorch. It offers a hands-on learning experience, allowing you to apply your knowledge through coding exercises and lessons so by the end of the course, you will possess the skills to build, train, and evaluate classification models using PyTorch. "Classification with PyTorch" is a part of a PyTorch Learning Path, check Prerequisites.
SyllabusÂ
- Linear Classifier and Logistic Regression
- Logistic Regression Prediction
- Bernoulli Distribution Maximum Likelihood Estimation
- Logistic Regression Cross Entropy
- Softmax Function
- Softmax PyTorch
Prerequisites
- Completion of PyTorch: Tensor, Dataset and Data Augmentation course
- Completion of Linear Regression with PyTorch course
Good understanding of PyTorch Tensors, DataSets and Linear Regression
Skills Prior to Taking this Course
- Basic knowledge of Python programming language.
- Basic knowledge of PyTorch Framework
- Familiarity with fundamental concepts of machine learning and deep learning is beneficial but not mandatory.