The Center for Brains, Minds and Machines (CBMM) is a premier institute and NSF Science and Technology Center dedicated to the study of intelligence. The website and Youtube channel of the institute contains a good number of tutorials and educational materials that help anyone interested in topics related to neuroscience, machine intelligence, etc. One of
RL Tutorial from Center for Brains Minds and Machines Read More »
Introduction Divide and conquer seem the most widely used strategy to attack hard problems. The use of this idea and similar approaches are ample in every discipline. In this post, let’s look at how this concept is a cornerstone in analyzing signals and systems. Consider the case of audio signals. We can think of them
The Art of Divide and Conquer Read More »
Nanotechnology deals with the science of building small, but why do we talk about such small things? Well, they ultimately constitute the world we live in and we can explore fascinating things with them, literally, it can shape the world around us. Properties of materials change due to quantum effects when they are made small,
A World of small things: Introduction to Nanotechnology 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
Hacking the Bivariate Gaussian Distribution Read More »
This article explains the minmax scaling operation using visual examples. 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
Visualizing MinMax Scaling Read More »
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
Gaussian Distribution Explained Visually Read More »
A Markov Decision Process (MDP) is a mathematical framework used to model decision-making situations where the outcome of a decision depends on both the current state of the system and the actions taken by the decision maker. In an MDP, the decision maker is represented as an agent, and the system is represented as a
Coding a Simple Markov Decision Process Read More »
Following is a list (in progress) of resources on Reinforcement Learning and allied topics. Though not comprehensive, it includes University lectures, YouTube playlists, MOOCs, blogs, etc. Hope this would be useful to someone getting started in reinforcement learning. UC Berkely CS 285 at UC Berkeley Deep Reinforcement Learning (23) Deep RL Bootcamp (15) CS 294:
Reinforcement Learning Resources Read More »
In this article, let us explore what is meant by the concept of orthogonality. Orthogonal or orthogonality is often introduced from a mathematical perspective. In general, most resources explains it in terms of linear algebra and vectors. One such example is when we learn about right-angled triangles the two sides are drawn as perpendicular or
What does it mean to say orthogonal? Read More »
“Small parts of curves are nearly straight line“ I heard this first-time years back in one of MIT’s OpenCourseWare calculus classes. Little did I know it is going to be a life-long lesson to me at that time. This concept is going to be one of the first principles we will be dealing with in
Small parts of curves are nearly straight line Read More »