Understand concepts like supervised and unsupervised learning, as well as the role of neural networks.
Python is the language of choice in AI. Familiarize yourself with Python and its data science libraries like TensorFlow and PyTorch.
Delve into neural networks, particularly deep neural networks. Learn about architectures, activation functions, and the backpropagation algorithm. This is the heart of AI.
FNLP is a crucial part of generative AI. Learn about tokenization, embeddings, and recurrent neural networks (RNNs).
Expand your knowledge with conditional GANs and style transfer techniques. These allow you to control the output of your generative models.
These could include generating art, deepfake detection, content recommendation systems, or even creating your own AI-powered applications.
Generative AI is a rapidly evolving field. Stay up-to-date with the latest research papers, attend conferences, and collaborate with the AI community