How to Get Started with ML APIs in Cancer Research?
If you are new to ML APIs, here are some steps to get started:
Identify Use Case: Determine the specific problem you aim to solve with ML, such as early detection or personalized treatment. Select Appropriate API: Choose an API that fits your needs, considering factors like ease of use, accuracy, and support. Prepare Data: Collect and preprocess the data you need, ensuring it is clean and relevant to your use case. Train and Evaluate: Use the selected API to build and train your model, then evaluate its performance using appropriate metrics. Deploy and Monitor: Deploy the model into a production environment and continuously monitor its performance.
