🤖 Machine learning models can be used in three ways on the web with TensorFlow.js.
🔄 The first way is to use pre-made models that have already been trained and can be reused for specific use cases.
🧠 These pre-made models are often robust, well-tested, and reliable for their given tasks.
🔍 Different machine learning models have varying levels of complexity and time requirements for training.
🔄 Transfer learning allows retraining pre-trained models to learn new tasks using custom data.
🔧 Creating your own models from scratch is another option in machine learning.
✨ TensorFlow.js allows you to create and train your own machine learning models from scratch.
⚡ You can use pre-made models or apply transfer learning to work with your own custom data.
🔧 This approach is useful when existing models are not suitable, slow, or memory-intensive.
🔑 TensorFlow.js now supports the execution of other forms of TensorFlow models.
🔑 There is a command line converter available to convert TensorFlow models to TensorFlow.js.
🔑 The next chapter will focus on pre-made models and coding examples.
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