Learn Neural Networks for Free: Courses and Resources for Image Generation

Generative neural networks enable the creation of images that can be used in art, design, game development, and even scientific research. Below is a selection of courses and tutorials that will help you delve deeper into this field.

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The course "Practical Deep Learning for Coders" presented by fast.ai and Jeremy Howard

This course offers a practical introduction to deep learning. The lessons cover the basics of building models for image generation, including GANs and transformers. The training is conducted based on the PyTorch framework, which makes the learning process convenient.

Duration: 8 lessons

The "Generative Adversarial Networks" course presented by DeepLearning.AI

In this course, you will learn to understand the main components of GANs and create basic generative networks using PyTorch. Later, by working with more complex models like DCGAN, as well as technologies such as Pix2Pix and CycleGAN, you will master GAN management.

Duration: 2 months

The "Deep Generative" specialization course presented by DeepLearning.AI

This program helps understand the fundamentals and future of deep learning and prepares you for developing advanced technologies. Using Python and TensorFlow, you will be able to solve real-world tasks such as speech recognition, machine translation, and image generation.

Duration: 3 months

The "Deep Generative Modeling" course presented by MIT

This course helps understand the basic principles of working with generative models. You will learn the differences between supervised and unsupervised learning, as well as the goals and capabilities of generative models.

Duration: 22 lessons

The "Building Neural Networks in Python" course presented by selfedu

This course is a practical guide designed to teach the basic principles of neural networks. Participants will become familiar with deep learning concepts, master Python tools such as TensorFlow and PyTorch, and learn to implement neural networks for tasks such as classification, regression, and image processing.

Duration: 33 lessons

The "Introduction to StyleGAN2" course presented by Classcentral

This course provides a detailed look at the principles of StyleGAN, one of the most popular GAN architectures. The features of StyleGAN, including style control and methods for generating high-quality images, are explained. The course is suitable for both beginners and experienced users interested in the field of image generation.

Duration: 14 lessons

The "Deep Learning with PyTorch, Keras and TensorFlow" course presented by IBM

This course covers the process of developing, training, and extending deep learning models using Python. You will work with images, text, and object recognition using Keras, PyTorch, and TensorFlow. The practical section includes building user-level layers, working with complex CNN models, and a final project for image classification analysis.

Duration: 4 months