Exploring the Application of Machine Learning on the Web with TensorFlow.js

🤖 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.