Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
https://cloud.google.com/tpu/docs/tutorials/resnet-alpha-py
https://cloud.google.com/tpu/docs/tutorials
https://towardsdatascience.com/running-pytorch-on-tpu-a-bag-of-tricks-b6d0130bddd4
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
https://github.com/drrb/java-rust-example
https://users.rust-lang.org/t/ffi-java-call-a-rust-dynamic-library/19924
https://docs.rs/jni/0.14.0/jni/
https://stackoverflow.com/questions/30258427/calling-rust-from-java
https://github.com/java-native-access/jna …
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
Regularization add a penalty term to the loss function in machine learning models. The type of regularizatin depends on the type of penalty used (not the type of the objective function …
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
L-BFGS converges faster and with better solutions on small datasets. However, ADAM is very robust for relatively large datasets. It usually converges quickly and gives pretty good performance. SGD with momentum …
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
If the objective function has derivative, then an optimization problem is equivalent to finding the root of the derivative of the object function.
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
It is suggested that you use the sklearn wrapper classes XGBClassifier and XGBRegressor
so that you can fully leverage other tools of the sklearn package.
There are 2 types of boosters …