diff --git a/Dockerfile.tmpl b/Dockerfile.tmpl
index 4b3dfee5..ae3f4e94 100644
--- a/Dockerfile.tmpl
+++ b/Dockerfile.tmpl
@@ -45,9 +45,11 @@ RUN uv pip install --no-build-isolation --system "git+https://github.com/Kaggle/
 
 # b/408281617: Torch is adamant that it can not install cudnn 9.3.x, only 9.1.x, but Tensorflow can only support 9.3.x.
 # This conflict causes a number of package downgrades, which are handled in this command
-RUN uv pip install --system --force-reinstall --extra-index-url https://pypi.nvidia.com pynvjitlink-cu12 cuml-cu12==25.2.1 \
-    nvidia-cudnn-cu12==9.3.0.75 scipy tsfresh
-RUN uv pip install --system --force-reinstall pynvjitlink-cu12==0.5.2
+# b/302136621: Fix eli5 import for learntools
+RUN uv pip install --system --force-reinstall --extra-index-url https://pypi.nvidia.com "cuml-cu12==25.2.1" \
+    "nvidia-cudnn-cu12==9.3.0.75" scipy tsfresh scikit-learn==1.2.2 category-encoders eli5
+
+RUN uv pip install --system --force-reinstall "pynvjitlink-cu12==0.5.2"
 
 # b/385145217 Latest Colab lacks mkl numpy, install it.
 RUN uv pip install --system --force-reinstall -i https://pypi.anaconda.org/intel/simple numpy
diff --git a/kaggle_requirements.txt b/kaggle_requirements.txt
index 3bc1dfd1..159a02e8 100644
--- a/kaggle_requirements.txt
+++ b/kaggle_requirements.txt
@@ -20,7 +20,6 @@ arrow
 bayesian-optimization
 boto3
 catboost
-category-encoders
 cesium
 comm
 cytoolz
@@ -33,7 +32,6 @@ deap
 dipy
 docker
 easyocr
-eli5
 emoji
 fastcore>=1.7.20
 fasttext
@@ -111,8 +109,6 @@ qtconsole
 ray
 rgf-python
 s3fs
- # b/302136621: Fix eli5 import for learntools
-scikit-learn==1.2.2
 # Scikit-learn accelerated library for x86
 scikit-learn-intelex>=2023.0.1
 scikit-multilearn