No module named 'sklearn'

Hi, in order to train a model I trained a dataset on Logistic Regression to start with and used that model in the below script but it gives me an error saying
“No module named ‘sklearn’” I have installed the package there but still doesn’t work. Can someone please tell me what can be done? Here is the script I found on this (Deploy a Python model (more efficiently) over Spark | by Schaun Wheeler | Towards Data Science)

import pyspark.sql.functions as f
import pyspark.sql.types as t
from pyspark.sql.window import Window as w

model = LogisticRegression(C=1e5), Y)

#creating test data from Pyspark
vectorAssembler = VectorAssembler(inputCols = [col for col in df.columns if '_id' not in col and 'label' not in col], outputCol="features")
features_vectorized = vectorAssembler.transform(df)

model_broadcast = sc.broadcast(model)
# udf to predict on the cluster
def predict_new(feature_map):
    ids, features = zip(*[
        (k,  v) for d in feature_map for k, v in d.items()
    ind = model_broadcast.value.classes_.tolist().index(1.0)
    probs = [
        float(v) for v in 
        model_broadcast.value.predict_proba(features)[:, ind]
    return dict(zip(ids, probs))
predict_new_udf = f.udf(
    t.MapType(t.LongType(), t.FloatType()
# set the number of prediction groups to create
nparts = 5000
# put everything together
outcome_sdf = (
                            f.create_map(f.col('id'), f.col('features')).alias('feature_map'), 
                            (f.row_number().over(w.partitionBy(f.lit(1)).orderBy(f.lit(1))) % nparts).alias('grouper')
                .select(f.explode(f.col('results')).alias('unique_id', 'probability_estimate'))

I am unaware a bit about clusters. So I read that I need to install sklearn on all clusters so I did ‘pip install -U scikit-learn’ and same for spark-sklearn as well. Can you help me run this?