S Leonardo Kap

Dark Matter and Dark Energy Research

[S Leonardo Kap @physicist_kap]

https://t.co/wtlQDZT7Ia
Fit your cosmological model with Supernova Data using MCMC in Python.
#DataScience #data_analysis #python #cosmology

[S Leonardo Kap @physicist_kap]

@jahanvi_t congratulations

[Massimo @Rainmaker1973]

The heart of an aircraft's artificial horizon is a gyroscope mounted in a double gimbal, which allows the aircraft to pitch and roll as the gyro stays vertically upright

[📹 aceaviations]
https://t.co/3qMdgX1AG1

[Himanshu Joshi @joshiphy]

Thats how my PhD started in 2010

[Historic Vids @historyinmemes]

Steve Jobs - “Start with quality”

[Nirmalya Kajuri @Kaju_Nut]

This thread is a beautiful demonstration of the art of back-of-envelope estimations using dimensional analysis.

Very instructive for all students of physics. I have met researchers who are very smart and rigorous, but end up working on poorly motivated problems because they did not know to back-of-envelope the problem first

[Swamp Thing @StringSwamp]

https://t.co/9LAndjB9PW

[Nirmalya Kajuri @Kaju_Nut]

Finally it's happening

[Dr Dan Jones @Hookean1]

Physics teachers. Ever fancied trying Cavendish's G experiment? 🙂
https://t.co/hufSGslnqJ

[Sahil Bloom @SahilBloom]

10 ideas that changed our lives (and may change yours):

Last Friday, we hosted an event in London in front of a sold out crowd of 500+ people.

The topic: 10 ideas that changed our lives.

Here were the ideas we shared:

1. There's no such thing as a loser who wakes up at 5am and works out.

A lot of success is determined by your own beliefs about yourself. When you're in a negative place, the most impactful action is the one that makes you self-identify as a winner. Waking up early and working out is hard. If you can do that, you're a winner. Winning begets more winning.

2. Energy is not finite.

Energy expands and contracts as a function of the activities you're engaged in. Certain activities are energy creating, certain activities are energy draining. Most of us spend too little time in our energy creating activities.

3. No one has it all figured out.

No one knows what they want to be when they grow up. Some are just a bit better at putting on a brave face, following their curiosity, and marching courageously into the unknown.

4. Direction over destination.

It is impossible (and rather anxiety-inducing) to attempt to determine your exact destination in life. Instead, focus on pointing your compass in the right direction. If you do that, you'll wind up where you were meant to be.

5. Focus on the WHO, not the HOW.

I no longer focus on the journey or the destination, I focus on the people. When you surround yourself with inspiring people, the journeys are more beautiful and the destinations are more brilliant.

6. Increase your luck surface area.

You can take actions that expand your odds of getting lucky. When choosing between two paths, always choose the path that has a larger luck surface area.

7. Default to trust.

In life, we all have a choice of whether to default to trust or skepticism. Always default to trust. When you occasionally get burned, view it as a tiny tax against all of the incredible benefit you will experience from this default setting.

8. The waiting room is always full.

Your "waiting room" of projects to tackle, people to see, and ideas to pursue will always be full. You will never make a dent in it. Do your best, work on energy creating activities, and have faith in the process.

9. The good old days are happening right now.

The "good old days" are happening right now. The life you're living today is something that your younger self would have dreamed of. You've done more than you think. Zoom out and reclaim perspective.

10. Time is your most precious asset.

Never let the quest for more distract you from the beauty of enough. Treat time as your ultimate currency. Spend it wisely, with those you love, in ways you’ll never regret.

***

Those 10 ideas changed our lives (and may change yours).

What were your favorites? What would you add to the list?

[Historic Vids @historyinmemes]

Christopher Nolan explaining the movie “Memento”

[Science girl @sciencegirl]

Physics at work

[Dan Go @CoachDanGo]

The 21 Rules of Life⁣
⁣
Written by Myamoto Musashi one week before his death. ⁣

[Nirmalya Kajuri @Kaju_Nut]

Taylor Swift as Loop Quantum Gravity books

[Sanjeev Varshney @skvdst]

#PDF #Fellowship at @IITHyderabad. Last date 26th February 2024

[S Leonardo Kap @physicist_kap]

@24hrlearns are madam ji upar niche 2 se multiply kr do . ye kya sikha rahi ho.. bewakoof q bna rahi ho baccho ko.. teach them some fundamentals.

[Priyadarshi Chakraborty @priya01101988]

Interested candidates can approach via email.

[Matt Dancho (Business Science) @mdancho84]

Bayes' Theorem is a fundamental concept in data science. But it took me 2 years to understand its importance. In 2 minutes, I'll share my best findings over the last 2 years exploring Bayesian Statistics. Let's go.

1. Background: "An Essay towards solving a Problem in the Doctrine of Chances," was published in 1763, two years after Bayes' death. In this essay, Bayes addressed the problem of inverse probability, which is the basis of what is now known as Bayesian probability.

2. Bayes' Theorem: Bayes' Theorem provides a mathematical formula to update the probability for a hypothesis as more evidence or information becomes available. It essentially describes how to revise existing predictions or theories in light of new evidence, a process known as Bayesian inference.

3. Bayesian Statistics: Bayesian Statistics is an approach to statistics that interprets probability as a measure of belief or certainty rather than just a frequency. This belief may be based on prior knowledge of the conditions that might be related to the event or experiment in question. This allows for making probabilistic statements about unknown parameters. For instance, instead of estimating a single value for a parameter, Bayesian statistics provides a distribution of possible values, reflecting the uncertainty.

4. Bayesian vs Frequentist: Bayesian inference is fundamentally about updating beliefs or probabilities as new data is observed, which can be very intuitive and aligns with how we often think about the world. Frequentist statistics interpret probability as the long-run frequency of events. The problem I have with frequentist approaches is that pre-determined distributions are used (e.g. Normal Gaussian), which does not always make sense.

5. Bayesian Machine Learning: Any time true confidence and probabilistic decision making is needed, Bayesian is the answer. Here are a couple of examples. Uncertainty Modeling: Unlike traditional machine learning methods that often provide point estimates, Bayesian methods focus on estimating distributions. Time-Series Analysis: Bayesian methods are particularly useful in time-series analysis, where uncertainty in the future is crucial.

6. Business Context: Businesses can use Bayes' Theorem to assess and quantify various risks, such as market risks, credit risks, or operational risks. By continuously updating the probability of risks as new information emerges, businesses can make more informed decisions.

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There’s a lot more to learning Data Science for Business. I’d like to help.

I put together a free on-demand workshop that covers the 10 skills that helped me make the transition to Data Scientist: https://t.co/LR39RJ5XKB

And if you'd like to speed it up, I have a live workshop where I'll share how to use ChatGPT for Data Science: https://t.co/EaMpKrJiqX

If you like this post, please reshare ♻️ it so others can get value.

[S Leonardo Kap @physicist_kap]

@ictstifr please paste the whole link.