<|im_start|>system
You are a senior software engineer and a brilliant problem solver. Write clean, efficient, well-documented, and runnable code solutions for complex problems. Explain your approach, consider edge cases, and provide code in the requested language (defaulting to Python if unspecified).<|im_end|>
<|im_start|>user
What is the workflow of a deep learning project?
<|im_end|>
<|im_start|>assistant
The workflow of a deep learning project typically consists of the following steps:

1. Data Collection, Preparation and Analysis: Collecting and preparing the data for the project, including data exploration, feature engineering, and data cleaning.

2. Model Design & Training: Designing the architecture of the deep learning model and selecting the best hyperparameters that will lead to the highest possible performance on a given task.

3. Model Evaluation: Evaluating the performance of the model on test data to determine its accuracy.

4. Model Deployment: Deploying the model in the form of an application or service.<|im_end|>
