deepchem · sudo-rsingh · Jan 31, 2024 · Jan 31, 2024 · Jan 31, 2024 · Jan 31, 2024
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
@@ -0,0 +1,5 @@
+{
+  "image": "mcr.microsoft.com/devcontainers/universal:2",
+  "features": {
+  }
+}
diff --git a/new-website/utils/tutorials/__pycache__/utils.cpython-310.pyc b/new-website/utils/tutorials/__pycache__/utils.cpython-310.pyc
diff --git a/new-website/utils/tutorials/acknowledgement.html b/new-website/utils/tutorials/acknowledgement.html
@@ -6,16 +6,43 @@
       padding-right: 80px;
       font-size: 50px;
     }
+    h2 {
+      margin-top: 250px;
+      padding-right: 80px;
+      font-size: 20px;
+    }
     .general {
       padding-left: 80px;
       padding-right: 80px;
       font-size: 20px;
     }
+    .citation {
+      padding-left: 80px;
+      padding-right: 80px;
+      font-size: 15px;
+    }
   </style>
   <body>
     <h1>Acknowledgement</h1>
     <p class='general'>
     We acknowledge the DeepChem community for their contributions and support.
     </p>
+    <p class='citation'>
+    <h2>Citing This Book:</h2>
+    <br>
+    @manual{
+    <br>
+    title={The DeepChem Book},
+    <br>
+    organization={DeepChem},
+    <br>
+    author={Ramsundar, Bharath and DeepChem Community},
+    <br>
+    howpublished = {\url{https://deepchem.io/tutorials}},
+    <br>
+    year={2024},
+    <br>
+    } 
+    </p>
   </body>
 </html>
diff --git a/new-website/utils/tutorials/acknowledgement.md b/new-website/utils/tutorials/acknowledgement.md
@@ -1,2 +1,13 @@
 # Acknowledgement
-We acknowledge the DeepChem community for their contributions and support.
+
+We acknowledge the DeepChem community for their contributions and support.
+
+Citing This Book:
+
+@manual{
+title={The DeepChem Book},
+organization={DeepChem},
+author={Ramsundar, Bharath and DeepChem Community},
+howpublished = {\url{https://deepchem.io/tutorials}},
+year={2024},
+}
diff --git a/new-website/utils/tutorials/build_pdf_book.py b/new-website/utils/tutorials/build_pdf_book.py
@@ -25,9 +25,9 @@
 from typing import List
 
 
-INFO_PATH = "/workspaces/deepchem.github.io/new-website/utils/tutorials/website-render-order/"
-DATA_PATH = "/workspaces/deepchem.github.io/new-website/utils/tutorials/html-notebooks/"
-PDF_PATH = "/workspaces/deepchem.github.io/new-website/utils/tutorials/storage/"
+INFO_PATH = "./website-render-order/"
+DATA_PATH = "./html-notebooks/"
+PDF_PATH = "./storage/"
 
 files = os.listdir(INFO_PATH)
 files = sorted(files)
@@ -48,7 +48,10 @@ def html_to_pdf():
         chapter = pd.read_csv(INFO_PATH + "-".join(i))
         for j in chapter["File Name"]:
             print(i, j)
-            pdfkit.from_file(DATA_PATH + j[:-5] + "html", PDF_PATH + j[:-5] + "pdf")
+            try:
+                pdfkit.from_file(DATA_PATH + j[:-5] + "html", PDF_PATH + j[:-5] + "pdf")
+            except:
+                pass
 
 def merge_pdf():
     """Merges the compiled PDFs."""

diff --git a/new-website/utils/tutorials/contents.html b/new-website/utils/tutorials/contents.html
@@ -19,7 +19,7 @@ <h2>1. Introduction To Deepchem</h2>
               <li>The Basic Tools of the Deep Life Sciences</li>
               <li>Working With Datasets</li>
               <li>An Introduction To MoleculeNet</li>
-              <li>Molecular Fingerprints</li>
+              <li>Molecular Fingerprints: Representing Molecules for Deep-Learning</li>
               <li>Creating Models with TensorFlow and PyTorch</li>
               <li>Introduction to Graph Convolutions</li>
               <li>Going Deeper on Molecular Featurizations</li>
@@ -33,89 +33,85 @@ <h2>1. Introduction To Deepchem</h2>
               <li>Training a Generative Adversarial Network on MNIST</li>
               <li>Advanced model training using hyperopt</li>
               <li>Introduction to Gaussian Processes</li>
-              <li>PytorchLightning Integration</li>
+              <li>Pytorch Lightning Integration for DeepChem Models</li>
           </ol>
       </li>
       <li>
-          <h2>2. Molecular Machine Learning</h2>
+          <h2>2. More Molecular Machine Learning</h2>
           <ol>
-              <li>Molecular Fingerprints
-              <li>Going Deeper on Molecular Featurizations
-              <li>Learning Unsupervised Embeddings for Molecules
-              <li>Atomic Contributions for Molecules
-              <li>Interactive Model Evaluation with Trident Chemwidgets
-              <li>Transfer Learning With ChemBERTa Transformers
-              <li>Training a Normalizing Flow on QM9
-              <li>Large Scale Chemical Screens
-              <li>Introduction to Molecular Attention Transformer
-              <li>Generating molecules with MolGAN
-              <li>Introduction to GROVER
+              <li>Going Deeper on Molecular Featurizations</li>
+              <li>Learning Unsupervised Embeddings for Molecules</li>
+              <li>Atomic Contributions for Molecules</li>
+              <li>Interactive Model Evaluation with Trident Chemwidgets</li>
+              <li>Transfer Learning With ChemBERTa Transformers</li>
+              <li>Training a Normalizing Flow on QM9</li>
+              <li>Large Scale Chemical Screens</li>
+              <li>Introduction to Molecular Attention Transformer</li>
+              <li>Generating molecules with MolGAN</li>
+              <li>Introduction to GROVER</li>
           </ol>
       </li>
       <li>
           <h2>3. Modeling Proteins</h2>
           <ol>
-              <li>Protein Deep Learning
+              <li>Protein Deep Learning</li>
           </ol>
       </li>
       <li>
           <h2>4. Protein Ligand Modeling</h2>
           <ol>
-              <li>Modeling Protein Ligand Interactions
-              <li>Modeling Protein Ligand Interactions With Atomic Convolutions
-              <li>DeepChemXAlphafold
+              <li>Modeling Protein Ligand Interactions</li>
+              <li>Applications of DeepChem with Alphafold: Docking and protein-ligand interaction from protein sequence</li>
           </ol>
       </li>
       <li>
           <h2>5. Quantum Chemistry</h2>
           <ol>
-              <li>Exploring Quantum Chemistry with GDB1k
-              <li>DeepQMC tutorial
-              <li>Training an Exchange Correlation Functional using Deepchem
+              <li>Exploring Quantum Chemistry with GDB1k</li>
+              <li>DeepQMC integration with DeepChem tutorial</li>
+              <li>Training an Exchange Correlation Functional using Deepchem</li>
           </ol>
       </li>
       <li>
           <h2>6. Bioinformatics</h2>
           <ol>
-              <li>Introduction to Bioinformatics
-              <li>Multisequence Alignments
-              <li>Deep probabilistic analysis of single-cell omics data
+              <li>Introduction to Bioinformatics</li>
+              <li>Multisequence Alignments</li>
+              <li>Deep probabilistic analysis of single-cell omics data</li>
           </ol>
       </li>
       <li>
           <h2>7. Material Sciences</h2>
           <ol>
-              <li>Introduction To Material Science
+              <li>Introduction To Material Science</li>
           </ol>
       </li>
       <li>
           <h2>8. Machine Learning Methods</h2>
           <ol>
-              <li>Using Reinforcement Learning to Play Pong
-              <li>Introduction to Model Interpretability
-              <li>Uncertainty In Deep Learning
+              <li>Using Reinforcement Learning to Play Pong</li>
+              <li>Introduction to Model Interpretability</li>
+              <li>Uncertainty In Deep Learning</li>
           </ol>
       </li>
       <li>
           <h2>9. Deep Differential Equations</h2>
           <ol>
-              <li>Physics Informed Neural Networks
-              <li>Introducing JaxModel and PINNModel
-              <li>About Neural ODE : Using Torchdiffeq with Deepchem
+              <li>Physics Informed Neural Networks</li>
+              <li>Introducing JaxModel and PINNModel</li>
+              <li>About Neural ODE : Using Torchdiffeq with Deepchem</li>
           </ol>
       </li>
       <li>
           <h2>10. Equivariance</h2>
           <ol>
-              <li>Introduction to Equivariance
-              <li>Modeling Protein Ligand Interactions With Atomic Convolutions
-              <li>DeepChemXAlphafold
+              <li>Introduction to Equivariance</li>
           </ol>
       </li>
       <li>
           <h2>11. Olfaction</h2>
           <ol>
-              <li>Predict Multi Label Odor Descriptors using OpenPOM
+              <li>Predict Multi Label Odor Descriptors using OpenPOM</li>
           </ol>
       </li>
   </ul>

diff --git a/new-website/utils/tutorials/contents.md b/new-website/utils/tutorials/contents.md
@@ -68,4 +68,4 @@
 1. Introduction to Equivariance
 
 ### 11. Olfaction
-1. Predict Multi Label Odor Descriptors using OpenPOM
+1. Predict Multi Label Odor Descriptors using OpenPOM
diff --git a/new-website/utils/tutorials/title.html b/new-website/utils/tutorials/title.html
@@ -21,7 +21,7 @@
   <body>
     <h1>The DeepChem Book</h1>
     <p class='general'>
-    Democratizing Deep-Learning for Drug Discovery Quantum Chemistry, Materials Science and Biology
+    Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
     </p>
     <p class='author'>
     Bharath Ramsundar