Change all TO DO to TODO

ArnNag · Nov 22, 2024 · 6072ad4 · 6072ad4
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Showing 5 changed files with 13 additions and 13 deletions.
diff --git a/Notebooks/Chap02/2_1_Supervised_Learning.ipynb b/Notebooks/Chap02/2_1_Supervised_Learning.ipynb
@@ -174,7 +174,7 @@
     {
       "cell_type": "code",
       "source": [
-        "# TO DO -- Change the parameters manually to fit the model\n",
+        "# TODO -- Change the parameters manually to fit the model\n",
         "# First fix phi1 and try changing phi0 until you can't make the loss go down any more\n",
         "# Then fix phi0 and try changing phi1 until you can't make the loss go down any more\n",
         "# Repeat this process until you find a set of parameters that fit the model as in figure 2.2d\n",

diff --git a/Notebooks/Chap06/6_5_Adam.ipynb b/Notebooks/Chap06/6_5_Adam.ipynb
@@ -185,11 +185,11 @@
         "    for c_step in range(n_steps):\n",
         "        # Measure the gradient as in equation 6.13 (first line)\n",
         "        m = get_loss_gradient(grad_path[0,c_step], grad_path[1,c_step]);\n",
-        "        # TO DO -- compute the squared gradient as in equation 6.13 (second line)\n",
+        "        # TODO -- compute the squared gradient as in equation 6.13 (second line)\n",
         "        # Replace this line:\n",
         "        v = np.ones_like(grad_path[:,0])\n",
         "\n",
-        "        # TO DO -- apply the update rule (equation 6.14)\n",
+        "        # TODO -- apply the update rule (equation 6.14)\n",
         "        # Replace this line:\n",
         "        grad_path[:,c_step+1] = grad_path[:,c_step]\n",
         "\n",
@@ -254,7 +254,7 @@
         "        v_tilde = v\n",
         "\n",
         "\n",
-        "        # TO DO -- apply the update rule (equation 6.17)\n",
+        "        # TODO -- apply the update rule (equation 6.17)\n",
         "        # Replace this line:\n",
         "        grad_path[:,c_step+1] = grad_path[:,c_step]\n",
         "\n",

diff --git a/Notebooks/Chap07/7_2_Backpropagation.ipynb b/Notebooks/Chap07/7_2_Backpropagation.ipynb
@@ -148,7 +148,7 @@
         "      all_h[layer+1] = all_f[layer]\n",
         "\n",
         "  # Compute the output from the last hidden layer\n",
-        "  # TO DO -- Replace the line below\n",
+        "  # TODO -- Replace the line below\n",
         "  all_f[K] = np.zeros_like(all_biases[-1])\n",
         "\n",
         "  # Retrieve the output\n",

diff --git a/Notebooks/Chap10/10_4_Downsampling_and_Upsampling.ipynb b/Notebooks/Chap10/10_4_Downsampling_and_Upsampling.ipynb
@@ -73,7 +73,7 @@
       "source": [
         "def subsample(x_in):\n",
         "  x_out = np.zeros(( int(np.ceil(x_in.shape[0]/2)), int(np.ceil(x_in.shape[1]/2)) ))\n",
-        "  # TO DO -- write the subsampling routine\n",
+        "  # TODO -- write the subsampling routine\n",
         "  # Replace this line\n",
         "  x_out = x_out\n",
         "\n",
@@ -159,7 +159,7 @@
         "# Now let's try max-pooling\n",
         "def maxpool(x_in):\n",
         "  x_out = np.zeros(( int(np.floor(x_in.shape[0]/2)), int(np.floor(x_in.shape[1]/2)) ))\n",
-        "  # TO DO -- write the maxpool routine\n",
+        "  # TODO -- write the maxpool routine\n",
         "  # Replace this line\n",
         "  x_out = x_out\n",
         "\n",
@@ -230,7 +230,7 @@
         "# Finally, let's try mean pooling\n",
         "def meanpool(x_in):\n",
         "  x_out = np.zeros(( int(np.floor(x_in.shape[0]/2)), int(np.floor(x_in.shape[1]/2)) ))\n",
-        "  # TO DO -- write the meanpool routine\n",
+        "  # TODO -- write the meanpool routine\n",
         "  # Replace this line\n",
         "  x_out = x_out\n",
         "\n",
@@ -316,7 +316,7 @@
         "# Let's first use the duplication method\n",
         "def duplicate(x_in):\n",
         "  x_out = np.zeros(( x_in.shape[0]*2, x_in.shape[1]*2 ))\n",
-        "  # TO DO -- write the duplication routine\n",
+        "  # TODO -- write the duplication routine\n",
         "  # Replace this line\n",
         "  x_out = x_out\n",
         "\n",
@@ -388,7 +388,7 @@
         "# The input x_high_res is the original high res image, from which you can deduce the position of the maximum index\n",
         "def max_unpool(x_in, x_high_res):\n",
         "  x_out = np.zeros(( x_in.shape[0]*2, x_in.shape[1]*2 ))\n",
-        "  # TO DO -- write the subsampling routine\n",
+        "  # TODO -- write the subsampling routine\n",
         "  # Replace this line\n",
         "  x_out = x_out\n",
         "\n",
@@ -460,7 +460,7 @@
         "  x_out = np.zeros(( x_in.shape[0]*2, x_in.shape[1]*2 ))\n",
         "  x_in_pad = np.zeros((x_in.shape[0]+1, x_in.shape[1]+1))\n",
         "  x_in_pad[0:x_in.shape[0],0:x_in.shape[1]] = x_in\n",
-        "  # TO DO -- write the duplication routine\n",
+        "  # TODO -- write the duplication routine\n",
         "  # Replace this line\n",
         "  x_out = x_out\n",
         "\n",

diff --git a/Notebooks/Chap21/21_1_Bias_Mitigation.ipynb b/Notebooks/Chap21/21_1_Bias_Mitigation.ipynb
@@ -328,7 +328,7 @@
       },
       "outputs": [],
       "source": [
-        "# TO DO -- try to change the two thresholds so the overall probability of getting the loan is 0.6 for each group\n",
+        "# TODO -- try to change the two thresholds so the overall probability of getting the loan is 0.6 for each group\n",
         "# Change the values in these lines\n",
         "tau0 = 0.3\n",
         "tau1 = -0.1\n",
@@ -393,7 +393,7 @@
       },
       "outputs": [],
       "source": [
-        "# TO DO -- try to change the two thresholds so the true positive are 0.8 for each group\n",
+        "# TODO --try to change the two thresholds so the true positive are 0.8 for each group\n",
         "# Change the values in these lines so that both points on the curves have a height of 0.8\n",
         "tau0 = -0.1\n",
         "tau1 = -0.7\n",