markdown revert

new-website/utils/tutorials/acknowledgement.md

@@ -0,0 +1,13 @@
+# Acknowledgement
+
+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},
+}

new-website/utils/tutorials/build_pdf_book.py

@@ -89,8 +89,8 @@ def compile_information_pages():
     pdfkit.from_file('acknowledgement.html', 'storage/acknowledgement.pdf')
 
 if __name__ == "__main__":
-    #os.system("mkdir " + PDF_PATH)
-    #html_to_pdf()
+    os.system("mkdir " + PDF_PATH)
+    html_to_pdf()
     merge_pdf()
-    #compile_information_pages()
-    #merge_pdf_pages(['storage/title.pdf', 'storage/acknowledgement.pdf', 'storage/contents.pdf', 'storage/full_pdf.pdf'])
+    compile_information_pages()
+    merge_pdf_pages(['storage/title.pdf', 'storage/acknowledgement.pdf', 'storage/contents.pdf', 'storage/full_pdf.pdf'])

new-website/utils/tutorials/contents.md

@@ -0,0 +1,70 @@
+
+### 1. Introduction To Deepchem
+1. The Basic Tools of the Deep Life Sciences
+2. Working With Datasets
+3. An Introduction To MoleculeNet
+4. Molecular Fingerprints
+5. Creating Models with TensorFlow and PyTorch
+6. Introduction to Graph Convolutions
+7. Going Deeper on Molecular Featurizations
+8. Working With Splitters
+9. Advanced Model Training
+10. Creating a high fidelity model from experimental data
+11. Putting Multitask Learning to Work
+12. Modeling Protein Ligand Interactions
+13. Modeling Protein Ligand Interactions With Atomic Convolutions
+14. Conditional Generative Adversarial Networks
+15. Training a Generative Adversarial Network on MNIST
+16. Advanced model training using hyperopt
+17. Introduction to Gaussian Processes
+18. PytorchLightning Integration
+
+### 2. Molecular Machine Learning
+1. Molecular Fingerprints
+2. Going Deeper on Molecular Featurizations
+3. Learning Unsupervised Embeddings for Molecules
+4. Atomic Contributions for Molecules
+5. Interactive Model Evaluation with Trident Chemwidgets
+6. Transfer Learning With ChemBERTa Transformers
+7. Training a Normalizing Flow on QM9
+8. Large Scale Chemical Screens
+9. Introduction to Molecular Attention Transformer
+10. Generating molecules with MolGAN
+11. Introduction to GROVER
+
+### 3. Modeling Proteins
+1. Protein Deep Learning
+
+### 4. Protein Ligand Modeling
+1. Modeling Protein Ligand Interactions
+2. Modeling Protein Ligand Interactions With Atomic Convolutions
+3. DeepChemXAlphafold
+
+### 5. Quantum Chemistry
+1. Exploring Quantum Chemistry with GDB1k
+2. DeepQMC tutorial
+3. Training an Exchange Correlation Functional using Deepchem
+
+### 6. Bioinformatics
+1. Introduction to Bioinformatics
+2. Multisequence Alignments
+3. Deep probabilistic analysis of single-cell omics data
+
+### 7. Material Sciences
+1. Introduction To Material Science
+
+### 8. Machine Learning Methods
+1. Using Reinforcement Learning to Play Pong
+2. Introduction to Model Interpretability
+3. Uncertainty In Deep Learning
+
+### 9. Deep Differential Equations
+1. Physics Informed Neural Networks
+2. Introducing JaxModel and PINNModel
+3. About Neural ODE : Using Torchdiffeq with Deepchem
+
+### 10. Equivariance
+1. Introduction to Equivariance
+
+### 11. Olfaction
+1. Predict Multi Label Odor Descriptors using OpenPOM