diff --git a/doc/gallery/applications/normalizing_flows_in_pytensor.ipynb b/doc/gallery/applications/normalizing_flows_in_pytensor.ipynb
index f8014bd0c6..ea49e8f8c8 100644
--- a/doc/gallery/applications/normalizing_flows_in_pytensor.ipynb
+++ b/doc/gallery/applications/normalizing_flows_in_pytensor.ipynb
@@ -34,7 +34,7 @@
     "- $f(\\cdot)$ if the (known!) PDF of the variable $X$\n",
     "- $G(\\cdot)$ is a function with nice properties.\n",
     "\n",
-    "The \"nice properties\" require (in the most general case) that $G(x)$ is a $C^1$ diffeomorphism, which means that it is 1) continuous and differentiable almost everywhere; 2) it is bijective, and 3) its derivaties are also bijective. \n",
+    "The \"nice properties\" require (in the most general case) that $G(x)$ is a $C^1$ diffeomorphism, which means that it is 1) continuous and differentiable almost everywhere; 2) it is bijective, and 3) its derivatives are also bijective. \n",
     "\n",
     "A simpler requirement is that $G(x)$ is continuous, bijective, and monotonic. That will get us 99% of the way there. Hey, $\\exp$ is continuous, bijective, and monotonic -- what a coincidence!\n"
    ]
@@ -412,7 +412,7 @@
    ],
    "source": [
     "z_values = pt.dvector(\"z_values\")\n",
-    "# The funtion `pm.logp` does the magic!\n",
+    "# The function `pm.logp` does the magic!\n",
     "z_logp = pm.logp(z, z_values, jacobian=True)\n",
     "# We do this rewrite to make the computation more stable.\n",
     "rewrite_graph(z_logp).dprint()"
@@ -668,7 +668,7 @@
    "id": "5f9a7a50",
    "metadata": {},
    "source": [
-    "Theese distribution are essentially the same."
+    "These distribution are essentially the same."
    ]
   },
   {
@@ -715,7 +715,7 @@
     "\n",
     "So, the inverse of their composition is $G^{-1} \\equiv (J^{-1} \\circ H^{-1}) = J^{-1}(H^{-1}(x)) = J^{-1}(\\ln(x)) = \\frac{\\ln(x) - a}{b}$\n",
     "\n",
-    "For the correction term, we need the determinant of the jacobian. Since $G$ is a scalar function, this is just the absolutel value of the gradient:\n",
+    "For the correction term, we need the determinant of the jacobian. Since $G$ is a scalar function, this is just the absolute value of the gradient:\n",
     "\n",
     "$$\\left | \\frac{\\partial}{\\partial x}G^{-1} \\right | = \\left | \\frac{\\partial}{\\partial x} \\frac{\\ln(x) - a}{b} \\right | = \\left | \\frac{1}{b} \\cdot \\frac{1}{x} \\right | $$\n",
     "\n",
@@ -733,7 +733,7 @@
    "source": [
     "### Solution by hand\n",
     "\n",
-    "We now implement theis analytic procesure in PyTensor:"
+    "We now implement this analytic procedure in PyTensor:"
    ]
   },
   {
@@ -803,7 +803,7 @@
    "id": "bcd081d3",
    "metadata": {},
    "source": [
-    "We can verify these values are exaclty what we are expecting:"
+    "We can verify these values are exactly what we are expecting:"
    ]
   },
   {
@@ -859,7 +859,7 @@
    "id": "46834a6f",
    "metadata": {},
    "source": [
-    "As above let's verify taht the results are consistent and correct:"
+    "As above let's verify that the results are consistent and correct:"
    ]
   },
   {