Molecular docking is an essential process in scientific drug discovery. By using the recent advances in generative deep learning the runtime required for such docking studies can be reduced significantly without comprimising accuracy compared to traditional methods. In this article, let us get familiarize ourselves with one open-source molecular docking codebase. The codebase named DiffDock …
It is often required for aspiring data scientists to do portfolio projects either to show their skills or just simply for the pure joy of doing it. In either cases, the complexity of the project can be often a small one to medium one. To truly convince the recruiters, it is often required to do …
Free Compute and Storage Resources for Machine Learning Projects Read More »
What are Support Vector Machines? Support Vector Machines (SVM) is one of the most elegant methods used for classification and regression in machine learning (ML). We can use SVM when we have a bunch of objects/features which we want to classify. SVM performs the classification by drawing a hyperplane (Figure.1) to separate each category of …
Essential Concepts and Implementation of Support Vector Machines Read More »
The Jupyter Notebook is best suited for doing as well as documenting empirical research. It can contain text, code images, videos, interactive content, and also nicely typesetting equations. This makes anyone doing simulations or empirical research prototype their work and share it with their colleagues. In this blog post, I am going to show how …
Visualizing 3D Protein Structures and Exporting Into images Using Jupyter Notebook. Read More »
Graphical User Interface (GUI) has been useful and easy to use for all types of computer users. We all use it every day to get things done. However, the computing history has the provision to do command-line instructions also to do the same things. Let us take a few examples where one beats the other. …
In STEM fields it is often required to communicate ideas using graphs or infographics. Many times the dimensionality of data will be higher and require clever hacks to represent so that the reader gets the idea quickly. There have been systematic studies on how to do data visualization effectively. For data scientists or machine learning …
Python Matplotlib Tip: Overlapping Curves and Multiple Axes Read More »
In one of our earlier posts, we have seen how we can visually relate the parts of the one-dimensional Gaussian distribution equation. In this post, we will follow the same strategy to understand the terms that comes up with a Multivariable Gaussian distribution. We will focus on the Bivariate Gaussian distribution as distributions of higher-order …
Normalization of vectors, an array of values, signals is often used as a preprocessing step before many algorithms. For example, in machine learning, some types of algorithms are prone to different inherent scales of features. In such situations normalization is done to give the same weightage to all features before passing it to the algorithm …
Gaussian distribution appears in various parts of science and engineering. Apart from a distribution often appear in nature, it has got important properties such as its relation to Central Limit Theorem (CLT). The figure above shows one-dimensional Gaussian distributions of various mean and variance values. Libraries like NumPy provide functions that can return Gaussian distribution …
This is a quick tutorial on how to implement a two-state Markov Decision Process (MDP). It has only two states: state 1 and state 2. Applications MDPs often appear in machine learning and reinforcement learning. At any stage, the agent can take any of the two actions. The actions are to stay or switch. The …