We are pleased to release Chapter 3 which focuses on how to train a ML model with your dataset, either using cloud services such as AWS Sagemaker or Roboflow, or using your own deployment. We discuss the pros and cons of both approaches. Specifically for Roboflow, we discuss an interesting option of transfer learning, where we use an existing trained model - the COCO image recognition model - and boost the model to recognize our Vector robots. While Roboflow offers a great service to train a model, it does not offer the flexibility to choose your own model. Using your own deployment, either via AWS Sagemaker or something that you have deployed, will enable you have more control on the model and code that you wish to use to train the model.
We are also using a new Beta feature from Substack, Substack Videos. The chapter is available via Substack Videos, which means that the content is available exclusively for our readers at www.learnwitharobot.com. Thank you for reading.
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