tensorflow_template_application

Why we included this project

For teams starting a TensorFlow project, this repo offers a complete, working skeleton instead of a set of disconnected examples. It reads data from CSV, LIBSVM, and TFRecords files, converts them into training input, then trains classification and regression models ranging from logistic regression to CNN and wide-and-deep. After training, it exports a SavedModel and serves predictions over gRPC or HTTP. The standout feature is the breadth of client bindings: Python, Java, Go, C++, Scala, Spark, Android, and iOS all have ready-made clients, so you can call the same trained model from a mobile app, a Java service, or a Spark job. The project also walks you through the engineering details you'd otherwise have to figure out on your own, like checkpoints, TensorBoard logging, dropout, batch normalization, learning-rate decay, and distributed training, all as runnable examples you can adapt to your own data.