diff --git a/new-website/utils/tutorials/acknowledgement.html b/new-website/utils/tutorials/acknowledgement.html index 4c82554a..29c15eaa 100644 --- 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; + }

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}, +
+ } +

\ No newline at end of file diff --git a/new-website/utils/tutorials/acknowledgement.md b/new-website/utils/tutorials/acknowledgement.md deleted file mode 100644 index 29c15eaa..00000000 --- a/new-website/utils/tutorials/acknowledgement.md +++ /dev/null @@ -1,48 +0,0 @@ - - - -

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}, -
- } -

- - \ No newline at end of file diff --git a/new-website/utils/tutorials/contents.md b/new-website/utils/tutorials/contents.md deleted file mode 100644 index 8513475f..00000000 --- a/new-website/utils/tutorials/contents.md +++ /dev/null @@ -1,71 +0,0 @@ -# Contents - -### 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