From 8ef3b129ba2e4d1626243ed4cebdd4968ef3e64e Mon Sep 17 00:00:00 2001 From: Rakshit Kumar Singh Date: Mon, 12 Feb 2024 16:12:16 +0000 Subject: [PATCH] markdown revert --- .../utils/tutorials/acknowledgement.md | 13 ++++ new-website/utils/tutorials/build_pdf_book.py | 8 +-- new-website/utils/tutorials/contents.md | 70 +++++++++++++++++++ 3 files changed, 87 insertions(+), 4 deletions(-) create mode 100644 new-website/utils/tutorials/acknowledgement.md create mode 100644 new-website/utils/tutorials/contents.md diff --git a/new-website/utils/tutorials/acknowledgement.md b/new-website/utils/tutorials/acknowledgement.md new file mode 100644 index 00000000..97b93ee7 --- /dev/null +++ b/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}, +} diff --git a/new-website/utils/tutorials/build_pdf_book.py b/new-website/utils/tutorials/build_pdf_book.py index abe67414..8c1cb400 100644 --- a/new-website/utils/tutorials/build_pdf_book.py +++ b/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']) diff --git a/new-website/utils/tutorials/contents.md b/new-website/utils/tutorials/contents.md new file mode 100644 index 00000000..ed3163c0 --- /dev/null +++ b/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 \ No newline at end of file