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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