Master Generative AI with 10+ Real-world Projects in 2025!
An introduction to generative adversarial networks and generative models. Beginners guide to understand how GANs work in computer vision.
Get started with deep learning with keras and tensorflow in r. Learn how to install keras with tensorflow in R & build a neural network model on MNIST dataset.
Learn about transfer learning, pre-trained models, their benefits, usage, fine-tuning techniques, and projects for identifying digits.
Deep learning applications for beginners using python. This article explains 5 deep learning applications using API and open source.
This article is a comparison between Keras and Theano. It also covers advanced techniques like transfer learning and fine tuning.
Introduction to neural art. In this article you will learn neural network painting and creating colorful images with AI generated art using Theano & keras.
A practical guide on handling structured and imbalanced datasets with deep learning. Learn deep learning experiments with KDD cup 1999 & MNIST datasets.
Learn when to apply TensorFlow neural networks, solve neural network problems, understand image data, and compare TensorFlow with other libraries.
A tutorial for convolution neural networks to identify images. Learn about deep learning for computer vision and implement CNNs using graphlab in python.
Image processing and feature selection can be tricky. This article teaches the basics of Python image processing and image feature extraction using Python.
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