diff --git a/AI-and-Analytics/Features-and-Functionality/IntelPython_XGBoost_Performance/IntelPython_XGBoost_Performance.ipynb b/AI-and-Analytics/Features-and-Functionality/IntelPython_XGBoost_Performance/IntelPython_XGBoost_Performance.ipynb
index 5ebc82f6bd..02420253a2 100755
--- a/AI-and-Analytics/Features-and-Functionality/IntelPython_XGBoost_Performance/IntelPython_XGBoost_Performance.ipynb
+++ b/AI-and-Analytics/Features-and-Functionality/IntelPython_XGBoost_Performance/IntelPython_XGBoost_Performance.ipynb
@@ -126,13 +126,14 @@
    "outputs": [],
    "source": [
     "def load_higgs(nrows_train, nrows_test, dtype=np.float32):\n",
-    "    if not os.path.isfile(\"./data/batch/HIGGS.csv.gz\"):\n",
+    "    if not os.path.isfile(\"./HIGGS.csv.gz\"):\n",
     "        print(\"Loading data set...\")\n",
     "        url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/00280/HIGGS.csv.gz\"\n",
     "        myfile = requests.get(url)\n",
-    "        open('./data/batch/HIGGS.csv.gz', 'wb').write(myfile.content)\n",
+    "        with open('./HIGGS.csv.gz', 'wb') as f:\n",
+    "            f.write(myfile.content)\n",
     "    print(\"Reading data set...\")\n",
-    "    data = pd.read_csv(\"./data/batch/HIGGS.csv.gz\", delimiter=\",\", header=None, compression=\"gzip\", dtype=dtype, nrows=nrows_train+nrows_test)\n",
+    "    data = pd.read_csv(\"./HIGGS.csv.gz\", delimiter=\",\", header=None, compression=\"gzip\", dtype=dtype, nrows=nrows_train+nrows_test)\n",
     "    print(\"Pre-processing data set...\")\n",
     "    data = data[list(data.columns[1:])+list(data.columns[0:1])]\n",
     "    n_features = data.shape[1]-1\n",