This course is suitable for all aspiring AI engineers who want to gain advanced knowledge on deep learning using PyTorch. It requires some basic knowledge of Python programming and basic …

Unlock the full potential of PyTorch with this comprehensive course designed for advanced users. Starting with Recommender Systems, you’ll explore how to build and evaluate these models, …

This course offers a comprehensive exploration of machine learning and deep learning using PyTorch and Scikit-Learn. It provides clear explanations, visualizations, and practical examples to help …

Advanced modules dive into PyTorch modeling, CNNs, RNNs, GANs, and more, ensuring you stay ahead in the rapidly evolving field of AI. With practical coding exercises and real-world applications, …

In this comprehensive course, you'll embark on a journey through the foundational elements and core concepts of PyTorch, one of the most popular deep learning frameworks.

This hands-on course will immerse you in the world of deep learning and computer vision using PyTorch. You'll gain a solid understanding of how PyTorch works, with a focus on creating deep …

This course is ideal for learners with experience in Python and a foundational understanding of machine learning and deep learning concepts who want to advance their skills in building neural networks with …

Course 3: In this course, you will use GANs for data augmentation and privacy preservation, survey more applications of GANs, and build Pix2Pix and CycleGAN for image translation.

You'll work hands-on with industry-standard tools including Scikit-learn, XGBoost, NLTK, PyTorch, and MLflow, learning how to implement and optimize advanced algorithms in real-world scenarios.

For this project, you’ll build and compare deep learning models using Keras and PyTorch, and work through a full development pipeline from data loading and augmentation to model training, …