Machine Learning with ChatGPT: Image Classification Model

About this guided project

In this 1-hour project, you will learn how to build a machine learning model using ChatGPT. We will use the MNIST database which is a large database of handwritten digits that is commonly used for training various image processing systems. You will be introduced to the process of fine-tuning, which involves adjusting the model's parameters to learn task-specific relationships between input and output. You will import the necessary libraries and load the data, and then split the data into training and testing sets. You will then define the model architecture, compile the model, and train it on the training data. After training, you will evaluate the model's performance on the testing data and make any necessary adjustments. This course is aimed at learners who are looking to get started with ChatGPT and explore how it can be used for coding and Machine Learning tasks. Prerequisites include a Google account and basic coding and machine learning knowledge. By the end of this project, you will have a solid understanding of how to build a machine learning model using ChatGPT. This project will provide you with step-by-step guidance through instructor-led videos. Unlike some other projects on Coursera, this experience will not utilize a virtual machine. Instead, learners will complete the project on their own browser or device.

What skills will you gain?

Keras (Neural Network Library)

Tensorflow

ChatGPT

Artificial Neural Networks

Applied Machine Learning

OpenAI

Generative AI

Artificial Intelligence and Machine Learning (AI/ML)

Deep Learning

Artificial Intelligence

Machine Learning Methods