deepmol

Contents:

  • Introduction
  • Google colabs to run AutoML
  • Available models
  • Installation
  • Input/output operations
  • Compound Standardization
  • Compound Featurization
  • Data Scaling
  • Feature Selection
  • Unsupervised Learning
  • Data Split
  • Unbalanced Datasets
  • Supervised Learning
  • Hyperparameter Optimization
  • Pipelines
  • Pipeline Optimization (AutoML)
  • Feature Importance
  • About Us
  • Related Publications
  • src
deepmol
  • Overview: module code

All modules for which code is available

  • deepmol.base.estimator
  • deepmol.base.predictor
  • deepmol.base.transformer
  • deepmol.datasets.datasets
  • deepmol.encoders.label_encoder
  • deepmol.encoders.label_one_hot_encoder
  • deepmol.evaluator.evaluator
  • deepmol.feature_selection.base_feature_selector
  • deepmol.imbalanced_learn.imbalanced_learn
  • deepmol.loggers.logger
  • deepmol.metrics.metrics
  • deepmol.metrics.metrics_functions
  • deepmol.models.deepchem_models
  • deepmol.models.models
  • deepmol.parallelism.multiprocessing
  • deepmol.scalers.base_scaler
  • deepmol.scalers.sklearn_scalers
  • deepmol.splitters.multitask_splitter
  • deepmol.splitters.splitters
  • deepmol.standardizer.basic_standardizer
  • deepmol.standardizer.chembl_standardizer
  • deepmol.standardizer.custom_standardizer
  • deepmol.standardizer.molecular_standardizer
  • deepmol.tokenizers.atom_level_smiles_tokenizer
  • deepmol.tokenizers.kmer_smiles_tokenizer
  • deepmol.tokenizers.tokenizer
  • deepmol.unsupervised.base_unsupervised
  • deepmol.unsupervised.umap
  • deepmol.utils.cached_properties
  • deepmol.utils.decorators
  • deepmol.utils.errors
  • deepmol.utils.utils

© Copyright 2024, João Correia and João Capela.

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