Add tutorials and usage examples

[j-adamczyk]

We should add example usage of molecular fingerprints, in particular:

1. Molecular property prediction (classification, regression, multioutput classification), with MoleculeNet and TDC benchmarks
2. Visualization and clustering
3. Virtual screening, e.g. with https://github.com/rdkit/benchmarking_platform

Those should also include computing fingerprints, tuning, and using parallelization. We should cover hashed fingerprints, descriptors, 3D variants with conformations etc.

Proposed tutorials list:

• introduction
• comparing different fingerprints (e.g. types, outputs, computation time)
• scikit-learn pipelines (e.g. concatenating fingerprints, normalizing, preprocessing)
• conformers and 3D fingerprints
• hyperparameter tuning
• different dataset splits
• loading built-in datasets, benchmarking
• distances and similarities, kNN, bulk functions
• custom fingerprints
• fingerprints for peptides, custom fingerprints using FASTA
• molecular filters, custom filters
• introduction to fingerprints and scikit-fingerprints for different backgrounds, e.g. chemists, chemoinformaticians, GNN researchers, ML scientists
• virtual screening, similarity searching, classification
• applicability domain checkers