We first go through how AI is a broad field of study that encompasses #MachineLearning as a sub-field.
We then break down Machine Learning into supervised and unsupervised models, using real-world examples to illustrate their functions and differences.
We move deeper into Deep Learning: Learn about artificial neural networks and the power of semi-supervised learning in applications like fraud detection in banking.
Then we delve into Generative AI, differentiating it from discriminative models and demonstrating its capabilities in creating new, innovative outputs.
Finally we walk through Large Language Models (LLMs) and uncover the significance of LLMs in AI, their pre-training processes, and their customization for specific industry applications
We then break down Machine Learning into supervised and unsupervised models, using real-world examples to illustrate their functions and differences.
We move deeper into Deep Learning: Learn about artificial neural networks and the power of semi-supervised learning in applications like fraud detection in banking.
Then we delve into Generative AI, differentiating it from discriminative models and demonstrating its capabilities in creating new, innovative outputs.
Finally we walk through Large Language Models (LLMs) and uncover the significance of LLMs in AI, their pre-training processes, and their customization for specific industry applications