diff --git a/tutorials/CMakeLists.txt b/tutorials/CMakeLists.txt
index 73a25a8557715..b2fb556f6b65c 100644
--- a/tutorials/CMakeLists.txt
+++ b/tutorials/CMakeLists.txt
@@ -315,13 +315,11 @@ else()
     list(APPEND tmva_veto machine_learning/envelope/classification.C)
   endif()
   #these depends on external packages
-  if (machine_learning-pymva)
-    ROOT_FIND_PYTHON_MODULE(torch QUIET)
-    ROOT_FIND_PYTHON_MODULE(keras QUIET)
-    ROOT_FIND_PYTHON_MODULE(sonnet QUIET)
-    ROOT_FIND_PYTHON_MODULE(graph_nets QUIET)
-    ROOT_FIND_PYTHON_MODULE(sklearn QUIET)
-  endif()
+  ROOT_FIND_PYTHON_MODULE(torch QUIET)
+  ROOT_FIND_PYTHON_MODULE(keras QUIET)
+  ROOT_FIND_PYTHON_MODULE(sonnet QUIET)
+  ROOT_FIND_PYTHON_MODULE(graph_nets QUIET)
+  ROOT_FIND_PYTHON_MODULE(sklearn QUIET)
   if (NOT BLAS_FOUND)
     list(APPEND tmva_veto machine_learning/TMVA_SOFIE_GNN_Application.C)
     list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RDataFrame.C)
@@ -336,14 +334,12 @@ else()
     list(APPEND tmva_veto machine_learning/TMVA_SOFIE_Models.py)
     list(APPEND tmva_veto machine_learning/TMVA_SOFIE_Inference.py)
     list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RSofieReader.C)
-    list(APPEND tmva_veto machine_learning/RBatchGenerator_TensorFlow.py)
   endif()
   if (NOT ROOT_SKLEARN_FOUND)
     list(APPEND tmva_veto machine_learning/TMVA_SOFIE_Models.py roofit/roofit/rf617_simulation_based_inference_multidimensional.py)
   endif()
   if (NOT ROOT_TORCH_FOUND)
     list(APPEND tmva_veto machine_learning/TMVA_SOFIE_PyTorch.C)
-    list(APPEND tmva_veto machine_learning/RBatchGenerator_PyTorch.py)
   endif()
   #veto this tutorial since it is added directly
   list(APPEND tmva_veto machine_learning/TMVA_SOFIE_GNN_Parser.py)
@@ -935,10 +931,25 @@ if(ROOT_pyroot_FOUND)
       analysis/dataframe/df035_RDFFromPandas.py
       roofit/roofit/rf409_NumPyPandasToRooFit.py)
   file(GLOB requires_keras   RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} machine_learning/keras/*.py)
-  file(GLOB requires_torch   RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} machine_learning/pytorch/*.py)
+  file(GLOB requires_torch   RELATIVE ${CMAKE_CURRENT_SOURCE_DIR}
+      machine_learning/pytorch/*.py
+      machine_learning/RBatchGenerator_PyTorch.py
+  )
   file(GLOB requires_xgboost RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} machine_learning/tmva10*.py)
   file(GLOB requires_sklearn RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} roofit/roofit/rf617*.py)
-  set(fixtureLists requires_numpy requires_numba requires_pandas requires_keras requires_xgboost requires_torch requires_sklearn)
+  file(GLOB requires_tensorflow RELATIVE ${CMAKE_CURRENT_SOURCE_DIR}
+      machine_learning/RBatchGenerator_TensorFlow.py
+  )
+  set(fixtureLists
+      requires_keras
+      requires_numba
+      requires_numpy
+      requires_pandas
+      requires_sklearn
+      requires_tensorflow
+      requires_torch
+      requires_xgboost
+  )
 
   # Now set up all the tests
   foreach(t ${pytutorials})
diff --git a/tutorials/machine_learning/TMVA_SOFIE_Models.py b/tutorials/machine_learning/TMVA_SOFIE_Models.py
index 5925ea497360d..469e22940c77c 100644
--- a/tutorials/machine_learning/TMVA_SOFIE_Models.py
+++ b/tutorials/machine_learning/TMVA_SOFIE_Models.py
@@ -41,7 +41,7 @@ def CreateModel(nlayers = 4, nunits = 64):
 
 def PrepareData() :
    #get the input data
-   inputFile = str(ROOT.gROOT.GetTutorialDir()) + "machine_learning/data/Higgs_data.root"
+   inputFile = str(ROOT.gROOT.GetTutorialDir()) + "/machine_learning/data/Higgs_data.root"
 
    df1 = ROOT.RDataFrame("sig_tree", inputFile)
    sigData = df1.AsNumpy(columns=['m_jj', 'm_jjj', 'm_lv', 'm_jlv', 'm_bb', 'm_wbb', 'm_wwbb'])
diff --git a/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.C b/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.C
index 0753e35d83c45..4f6a731c22966 100644
--- a/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.C
+++ b/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.C
@@ -34,7 +34,7 @@ using namespace TMVA::Experimental;
 void TMVA_SOFIE_RDataFrame(int nthreads = 2){
 
    std::string inputFileName = "Higgs_data.root";
-   std::string inputFile = gROOT->GetTutorialDir() + "/machine_learning/data/" + inputFileName;
+   std::string inputFile = std::string{gROOT->GetTutorialDir()} + "/machine_learning/data/" + inputFileName;
 
    ROOT::EnableImplicitMT(nthreads);
 
diff --git a/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.py b/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.py
index 1b23d0b7d607c..6185684f31b66 100644
--- a/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.py
+++ b/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.py
@@ -37,7 +37,7 @@
 ROOT.gInterpreter.Declare('auto sofie_functor = TMVA::Experimental::SofieFunctor<7,TMVA_SOFIE_'+modelName+'::Session>(0,"Higgs_trained_model_generated.dat");')
 
 # run inference over input data
-inputFile = str(ROOT.gROOT.GetTutorialDir()) + "machine_learning/data/Higgs_data.root"
+inputFile = str(ROOT.gROOT.GetTutorialDir()) + "/machine_learning/data/Higgs_data.root"
 df1 = ROOT.RDataFrame("sig_tree", inputFile)
 h1 = df1.Define("DNN_Value", "sofie_functor(rdfslot_,m_jj, m_jjj, m_lv, m_jlv, m_bb, m_wbb, m_wwbb)").Histo1D(("h_sig", "", 100, 0, 1),"DNN_Value")
 
diff --git a/tutorials/machine_learning/TMVA_SOFIE_RDataFrame_JIT.C b/tutorials/machine_learning/TMVA_SOFIE_RDataFrame_JIT.C
index 5a1326c1d83aa..0969f5f33b4ea 100644
--- a/tutorials/machine_learning/TMVA_SOFIE_RDataFrame_JIT.C
+++ b/tutorials/machine_learning/TMVA_SOFIE_RDataFrame_JIT.C
@@ -68,7 +68,7 @@ void TMVA_SOFIE_RDataFrame_JIT(std::string modelFile = "Higgs_trained_model.h5")
     CompileModelForRDF(modelHeaderFile,7);
 
     std::string inputFileName = "Higgs_data.root";
-    std::string inputFile = gROOT->GetTutorialDir() + "/machine_learning/data/" + inputFileName;
+    std::string inputFile = std::string{gROOT->GetTutorialDir()} + "/machine_learning/data/" + inputFileName;
 
     ROOT::RDataFrame df1("sig_tree", inputFile);
     auto h1 = df1.Define("DNN_Value", "sofie_functor(rdfslot_,m_jj, m_jjj, m_lv, m_jlv, m_bb, m_wbb, m_wwbb)")
diff --git a/tutorials/machine_learning/TMVA_SOFIE_RSofieReader.C b/tutorials/machine_learning/TMVA_SOFIE_RSofieReader.C
index 3fcbf372c36f0..46763fae5e153 100644
--- a/tutorials/machine_learning/TMVA_SOFIE_RSofieReader.C
+++ b/tutorials/machine_learning/TMVA_SOFIE_RSofieReader.C
@@ -39,7 +39,7 @@ void TMVA_SOFIE_RSofieReader(){
    // predict model now on a input file using RDataFrame
 
    std::string inputFileName = "Higgs_data.root";
-   std::string inputFile = gROOT->GetTutorialDir() + "/machine_learning/data/" + inputFileName;
+   std::string inputFile = std::string{gROOT->GetTutorialDir()} + "/machine_learning/data/" + inputFileName;
 
 
    ROOT::RDataFrame df1("sig_tree", inputFile);