Free online courseDeep Learning With PyTorch

Course Description

Dive into the world of deep learning with Codemy's comprehensive course, Deep Learning With PyTorch. As a premier introduction to artificial intelligence, this course guides you through the essentials of using PyTorch, an open-source machine learning library. Embark on your deep learning journey with an immersive exploration of PyTorch and unlock powerful capabilities for handling deep learning tasks.

Begin your adventure with an overview of deep learning concepts, ensuring a solid foundation before delving into PyTorch's tensor functionalities. Master tensor operations, reshaping, slicing, and mathematical transformations that form the basis for building efficient neural networks.

From creating a basic neural network model to loading data and training your model, gain hands-on experience and set the stage for evaluating real-world data. Learn to leverage the power of evaluation techniques for test datasets and apply the network to new data scenarios.

Further your skills with modules on saving and loading neural network models, essential for real-world applications. Transition into more advanced topics by exploring convolutional neural networks (CNNs), pivotal in tasks such as image recognition and processing. Understand convolutional layers, RGB integration, and pooling layers within CNNs, vital for optimizing neural network performance.

The course emphasizes the practical implementation of concepts, demonstrated through the import of MNIST images and the development of a robust CNN model that is trained and tested. Visualize your results with sophisticated graphing techniques, culminating in the capability to send new images through your trained models and enhance CNN analysis.

Whether you're a novice stepping into artificial intelligence or an IT professional seeking to expand your expertise, this engaging online course provides valuable insights and skills crucial for career development in the tech industry. Immerse yourself in the nuances of PyTorch, from basic neural networks to convolutions, and prepare to harness the transformative power of deep learning.