NVIDIA/cuml v24.12.00 on GitHub

🚨 Breaking Changes

Fix SSL error. (#6177) @bdice
Fix scikit-learn version specifier (#6158) @trxcllnt
Correctly handle missing categorical data in experimental FIL (#6132) @wphicks
Put a ceiling on cuda-python (#6131) @bdice
Don't presume pointers are mutually exclusive for device/host. (#6128) @robertmaynard
cuml SINGLEGPU now tells cuvs to not build with nccl/mg support (#6127) @robertmaynard
Remove type from pickle header for CumlArray (#6120) @wphicks
Forward merge Branch 24.10 into 24.12 (#6106) @divyegala
Fix Dask estimators serialization prior to training (#6065) @viclafargue

Update FIL tests to use XGBoost UBJSON instead of binary (#6153) @hcho3
Use sparse knn / distances from cuvs (#6143) @benfred
Ensure MG to have the same number of allreduce calls in mean_stddev for sparse matrix to avoid hanging (#6141) @lijinf2
Stop excluding cutlass from symbol exclusion check (#6140) @vyasr
Optimize MG variance calculation for dataset standardization for logistic regression (#6138) @lijinf2
enforce wheel size limits, README formatting in CI (#6136) @jameslamb
Experimental command line interface UX (#6135) @dantegd
add telemetry (#6126) @msarahan
Make cuVS optional if CUML_ALGORITHMS is set (#6125) @hcho3
devcontainer: replace VAULT_HOST with AWS_ROLE_ARN (#6118) @jjacobelli
print sccache stats in builds (#6111) @jameslamb
fix version in Doxygen docs (#6104) @jameslamb
make conda installs in CI stricter (#6103) @jameslamb
Make get_param_names a class method on single GPU estimators to match Scikit-learn closer (#6101) @dantegd
Prune workflows based on changed files (#6094) @KyleFromNVIDIA
Update all rmm imports to use pylibrmm/librmm (#6084) @Matt711
Merge branch 24.10 into branch 24.12 (#6083) @jameslamb