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Shy people are either overthinking or highly observant of the social setting.

And in many cases it can be both.

'So what do I do?'

You learn the 75/25 law.

'What is that?'

The law of charisma...👇

Let's address the over thinkers first.

Do you have any idea why you overthink?

'Yea. Because others are judging how shy I am.'

Incorrect.

Others are thinking about themselves, not you.

But the fact that you think they are thinking about you, you fuck up the interaction.

Now you stay in your head too much & avoid the present moment.

A major no no in the social world.

Your tendency to think that others are judging you for being shy, coincidentally makes you more shy.

And that's when you start giving off a strange vibration to the social setting.

This is when you begin attracting comments like 'why are you so quiet?'

This is my son, Sam. He’s 5. And today he learned how shitty and harmful #ToxicMasculinity is. My rage meter is spiking right now so excuse me if this is a little raw but there are some things I want to say about BS #gender norms (a thread)

Sam is my middle child & he’s a terror. A “boy’s boy” as so many (not me) would say. He’s rough and tumble, he’s loud, he’s always dirty, loves trucks, plays sports and knee drops me from the couch. But he also loves a lot of “girl” things.

Sam has a collection of purses because he likes to carry things around. And he also loves to have his nails painted bright colors because he thinks they “look beautiful.” And he’s right – they are beautiful…

So he proudly wore his red nail polish to kindergarten this morning because Sam has absolutely no concept of nail polish only being for girls or reason to think anyone would possibly have a problem with beautiful nails.

But his classmates did have a problem. A big one. Sam was ridiculed for being a boy with nail polish. They called him names and told him to take it off. This lasted the entire day.

MAHARAANI TARARANI: THE QUEEN OF MARATHAS

Rani Tarabai was the brave daughter-in-law of Chhatrapati Shivaji and one of the greatest medieval Monarchs India ever had.
She was born in 1675 to one of the bravest commander-in-chiefs of Shivaji's Army named Hambir Rao Mohite.

Tarabai was just 8yrs old when she was married to Shivaji's younger son, Rajaram. Mughals and Marathas were constantly at war with each other. Shivaji was crowned the ruler of the Independent Maratha Swarajya in 1674 which was established by him.

However,the great leader died in 1680&the Maratha Samrajya went into a complete&total chaos.Marathas saw some very tough times ahead. In 1689,when Raigad Fort fell to the Mughal Army of over 15000,Shivaji's first wife Saibai and his elder son Sambhaji were captured&put to death.

Sambhaji's wife and son Shahu were taken prisoners to the Mughal court. During the same battle, Shivaji's second son Rajaram(Tarabai's husband) , who was the heir to the throne now, managed to escape using a disguise. He made his way to the Gingee Fort in Tamil Nadu.

Mughal General Zulfikar Khan, however, followed them to Gingee laying siege to the Gingee Fort. From 1690-1698,This was the longest siege by a Mughal Army of any Fort which stands testimony to the military and diplomatic credentials of Rani Tarabai.

Important paper from Google on large batch optimization. They do impressively careful experiments measuring # iterations needed to achieve target validation error at various batch sizes. The main "surprise" is the lack of surprises. [thread]

https://t.co/7QIx5CFdfJ

The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.

They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.

When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.

Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.

Technical Analysis Masterclass- Part 2

'Entering the trade'

Entering a trade without ascertaining a certain things is gambling.

In this masterclass we will learn the pre-requisites to enter a trade.

DON'T ENTER A TRADE WITHOUT DETERMINNG THE FOLLOWING.

Please share.

We understand what reward to risk (popularly called risk to reward) is.
It will be denoted by R:R.

We will also try to bust a few myths about R:R and how to avoid losing trades.

Before entering a trade, you need to determine 3 things.

1. Entry trigger
2. Stop loss
3. Target

1. Entry trigger = Reasons for entering a trade. There could be multiple reasons or a single reason for entry.

Generally a set of reasons AKA confluence is a higher probability trade and a generally a safer entry.

Example of an entry trigger.

2. Stop Loss.

The price in the opposite direction of the trade where the trade is exited, at a loss.

At this level, the reason for the entry becomes invalidated according to TA and the price can then move in the opposite direction, probabilistically.

3. Target is the possible price level that the asset might touch based on previous trends or confluence AND where a possible reversal could occur.

Target is the next path of least resistance from where the price might reverse.

We will always ONLY use TA to determine all 3.