What does "Training Procedures" mean?
Table of Contents
Training procedures are important steps used to teach computers how to do tasks, like recognizing actions in videos or understanding images. These procedures involve several key parts that help improve the computer’s ability to learn from data.
Data Collection
The first step is gathering data. This data can come from videos, images, or other sources. For example, videos might show people moving or performing actions. The quality and variety of this data are important because they help the computer learn better.
Pre-processing
Next, the data needs to be prepared. This can involve cleaning the data, removing unnecessary parts, and making sure it’s in a format that the computer can use. For instance, images may need to be resized, and videos may be split into shorter segments.
Model Selection
Once the data is ready, the next step is choosing a model. A model is like a set of rules or a map that helps the computer make decisions based on the data. Different models can be good for different tasks, so selecting the right one is crucial.
Training the Model
After choosing a model, training begins. This means showing the model the data repeatedly while adjusting it to improve its performance. During training, the model learns to recognize patterns or actions and gets better over time.
Evaluation
After training, it’s important to test how well the model works. This usually involves using a separate set of data that the model hasn’t seen before. This helps ensure the model can perform well in real-life situations, not just with the training data.
Fine-tuning
Sometimes, even after testing, the model might need some adjustments. This process, known as fine-tuning, helps improve the model’s accuracy and performance by tweaking its settings or providing additional training.
Conclusion
In summary, training procedures are essential to help computers learn effectively from data. By following these steps, models can accurately perform tasks like understanding actions in videos or analyzing images.