smostafanejad commited on
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3167707
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1 Parent(s): 0ed304d

fixes the broken links for images

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  1. 02_bcce_2024.ipynb +4 -4
02_bcce_2024.ipynb CHANGED
@@ -120,7 +120,7 @@
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  "\n",
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  "Consider the molecule ethanol. The image below shows a representation that we are used to seeing in chemistry:\n",
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  "\n",
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- "![ethanol](Images/ethanol.png)\n",
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  "\n",
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  "However, the SMILES representation of this molecule would be \"CCO\".\n",
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  "\n",
@@ -161,11 +161,11 @@
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  "### SMILES Examples\n",
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  "\n",
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  "<div style=\"text-align:center;\">\n",
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- " <img src=\"Images/smiles_example_1.png\" style=\"display: block; margin: 0 auto; max-height:300px;\">\n",
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  "</div>\n",
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  "\n",
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  "<div style=\"text-align:center;\">\n",
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- " <img src=\"Images/smiles_example_2.png\" style=\"display: block; margin: 0 auto; max-height:300px;\">\n",
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  "</div>\n",
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  "\n",
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  "### Using Online Resources\n",
@@ -646,7 +646,7 @@
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  "The next step after the data preparation is to build and train our random forest regression model. A random forest is a decision tree model that uses a \"forest\" of multiple decision trees and randomly chooses which variables to use in each tree. Generally, each individual tree is not that good at making a prediction, but collectively the trees are quite good at making predictions. Note that each tree predicts an individual value and then a vote is taken (in the case of regression, an average of the predicted values) to determine the final predicted value.\n",
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  "\n",
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  "<div style=\"text-align:center;\">\n",
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- " <img src=\"Images/Random_forest_explain.png\" style=\"display: block; margin: 0 auto; max-height:400px;\">\n",
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  "</div>\n",
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  "\n",
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  "### Hyperparameters\n",
 
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  "\n",
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  "Consider the molecule ethanol. The image below shows a representation that we are used to seeing in chemistry:\n",
122
  "\n",
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+ "![ethanol](images/ethanol.png)\n",
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  "\n",
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  "However, the SMILES representation of this molecule would be \"CCO\".\n",
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  "\n",
 
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  "### SMILES Examples\n",
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  "\n",
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  "<div style=\"text-align:center;\">\n",
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+ " <img src=\"images/smiles_example_1.png\" style=\"display: block; margin: 0 auto; max-height:300px;\">\n",
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  "</div>\n",
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  "\n",
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  "<div style=\"text-align:center;\">\n",
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+ " <img src=\"images/smiles_example_2.png\" style=\"display: block; margin: 0 auto; max-height:300px;\">\n",
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  "</div>\n",
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  "\n",
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  "### Using Online Resources\n",
 
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  "The next step after the data preparation is to build and train our random forest regression model. A random forest is a decision tree model that uses a \"forest\" of multiple decision trees and randomly chooses which variables to use in each tree. Generally, each individual tree is not that good at making a prediction, but collectively the trees are quite good at making predictions. Note that each tree predicts an individual value and then a vote is taken (in the case of regression, an average of the predicted values) to determine the final predicted value.\n",
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  "\n",
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  "<div style=\"text-align:center;\">\n",
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+ " <img src=\"images/Random_forest_explain.png\" style=\"display: block; margin: 0 auto; max-height:400px;\">\n",
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  "</div>\n",
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  "\n",
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  "### Hyperparameters\n",