No prior knowledge required — just common sense and a brain

As a 16 year old new to machine learning, I came across a ton of acronyms which had absolutely no meaning: PCA, SVD, MLP, etc. It’s almost like FDR’s alphabet soup from WWII (CCC, WPA, PWA (for all you history buffs ;)). It just blew my mind how tons of sources and in professional academia papers outlined the same exact definition but didn’t explain what this core machine learning concept ultimately meant:

Stalling The More Permanent Future Pandemic We Still Can Prevent

You’re a tourist visiting India for the first time. You’ve had a great time so far, chatting with the locals and building a great relationship, trying new food, and visiting landmark tourist destinations that’ve been on your bucket list for quite some time. You get back to your cottage in the village you’re staying in, and suddenly you don’t feel right. Something doesn’t feel right.

As you start feeling sick, you ask for the locals to direct you to the nearest hospital and doctors who might be able to treat you.

It turns out you have an antibacterial infection. But…

Ok. So 2020 wasn’t what we all expected it to be….

Many of my new year's resolutions/goals from last year involved traveling to different countries to spend time in nature and attending my favorite conferences in person. I couldn’t make those happen, but I’m still happy with the way that 2020 turned out. Instead of looking outwards, I took a lot more time working to work on my own personal growth and development as opposed to focusing on optimizing external metrics.

Top reflection topics from 2020

  1. Consistency over intensity — How to set better goals
  2. Live life in the present
  3. The small things matter
  4. Why…

2020 has objectively been a hard time for science, with the rearrangement of project priorities and funding and the lack of serendipitous in-person conversations at conferences. We won’t have pictures like those taken at the Solvay conference, scientists shoulder to shoulder. However, we do have Zoom screenshots, and that’ll do :)

I recently had the amazing opportunity to attend the Harvard-Stanford Symposium on Drug discovery! Topics ranged from domain extrapolation in chemical spaces to protein-protein interaction (PPI) prediction studies and design of COVID diagnostics. Below are the summaries of the individual talks.

Regina Barzilay — MIT

Professor Barzilay talked about how there are four…

An attempt at answering humanity’s (arguably) most important question through the lens of a 17th-century philosopher

An Introduction to the Classic Descartes Story

What if everything that you’re seeing in front of you is completely false? Sounds absurd, but the truth is, there’s no way to deny it. You could be dreaming, or maybe we’re in some sort of simulation where we’re being programmed to think in certain ways. Again — these thoughts are quite absurd. But, there’s no way to absolutely prove or disprove these ideas, and that’s why we can’t put them aside. This is the way that René Descartes, a 17th-century philosopher, mathematician, and natural scientists started questioning everything that he thought or believed. He saw his beliefs and logical…

On Eternal Recurrence, Dimorphism, and Superhumans

When you think about people in history who went against the rest of society to conceive of an ultimate truth, what often comes to mind? Most people might of think of Galilelo Galilei or Nicolas Copernicus, who were declared heretics for promoting the heliocentric model, a model that seemed to directly contradict pre-existing Christian doctrines.

One name that might not immediately come to mind for most is Friedrich Nietzche; nevertheless, he most clearly defied societal norms. …

Why is it that we still haven’t been able to figure out how to cure diseases like Alzheimer’s? It’s mainly because:

  1. We don’t understand the main mechanism of the disease (the pathways involved in misfolded amyloid accumulation). That means that when we choose a target, we’re not entirely sure if it is ‘druggable’ — that is — whether it will have the effect that we intend it to have.
  2. We don’t entirely understand the relationship between small molecule structure and physiological properties and side effects.

We’ll see more generally how machine learning is allowing us to get a better shot…

Stealing the most rewards 👀🏆 using reinforcement learning

In this article, I go over the basics of reinforcement learning and the BANDIT algorithm along with explained code implementations. Skip the first section if you’d like to jump to the code implementations.


Imagine that you’re playing games at a casino and you have multiple slot machines that you can hedge your bets on — say 10 machines.

How do you know which machines to start with? And how do you know which machines to select after if your objective is to maximize reward?

This is the commonly stated multi-armed BANDIT problem within Reinforcement learning.

Reinforcement learning itself is commonly…

Get an Intuition for the Difference between SGD vs RMSprop vs Adam optimizers

Smooth loss landscape visualization. Credit —

When people first start out machine learning in PyTorch, you might see a PyTorch script like this.

Let’s decipher the black box — A Simple Explanation to Force Field functions like CHARMM, programs like Rosetta, and cutting-edge Deep Learning Algorithms

If you thought about each of our cells like a miniature city, our proteins would play every role from transportation to housing, from banking to agriculture. They have complex three-dimensional structures and they do pretty much everything in our cells. I’d argue that our proteins should receive more attention than our genome because our genome is ironically the simplest parts of who we here. As information propagates through the transcriptome (RNA) to the proteome, our cells get more and more complex, and that’s why protein structures are crucial to try and decipher this complexity.

Of course — one of the…

Mukundh Murthy

Innovator passionate about the intersection between structural biology, machine learning, and chemiinformatics. Currently @ 99andbeyond.

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