Likelihood Funtion simply explained
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It represents the probability of observing the given data, given a particular set of parameter values. It plays a crucial role in Bayes
Blog posts
2025
Introduction to Bayes
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In very few words, Bayes is a framework for reasoning about uncertainty using probability. The core idea is that we update our beliefs about an hypothesis as we gather more and more data (evidence) .
2024
Introduction to Unittesting
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Why use Unit Testing?
Unittesting for any serious project is mandatory, not optional. It’s a good negative indicator -i.e. it points out poor-quality code with relatively high accuracy-. If the code is hard to unit test, it’s a strong sing that the code needs improvement.
Laplacian Positional Encoding
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Laplacian Positional Encoding
Harris Detector
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Widely used for corner detection in computer
Sequence Types
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Built-in Sequences in Python
Python provides several built-in sequence types that are implemented in C, which are divided into two categories based on how they store their contents: Container sequences and Flat sequences.
Dunder Methods
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What are special methods?
They are ‘predefined’ methods that allow you to customize the behavior of classes. Can also be referred to as “dunder” (double-underscore) methods.
KNN-Graph
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Let’s say we have a dataset of 10 molecules (A through J), and we want to construct a 3-NN graph (k=3) where k indicates the number of neighbours.
TMAP
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The general process of TMAP looks like this:
LSH Forest
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Locality-sensitive hashing or LSH, allows us to focus on pairs that are likely to be similar, instead of having to look at all pairs possible. It reduces therefore the amount of computational time required by a brute force approach.
MinHashing
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TL;DR: MinHashing is a way to reduce the dimensionality of fingerprints. Instead of comparing 512-bit vectors directly -these are the vectors that we obtain after the fingerprint is applied to a SMILES format molecule-, MinHash reduces these vectors to smaller hashes that preserve similarity between molecules.
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