@AnyBodyCanFly Created this thread in 2018, as saw this coming. Covid actually accelerated the trend … next disruption will be lead by biosciences. Unseen today be seen few years out

MEENAKSHI AMMAN, MADURAI (TN)
#bharatmandir #navratri2021

A paadal Petra sthalam where Shiva took the form of Sundareswarar (the handsome one) and married Devi Parvati (Meenakshi).
Devi is also known by the name Angayarkanni (mother with the beautiful fish eyes).
@GunduHuDuGa

Devi Meenakshi emerged from yagna fire as a 3 year old girl when Pandyan King Malayadwaja and Kanchanamalai were praying for a child.
It is said that Devi was born with three breasts and there was a prophesy that her superfluous breast would melt away when she met her husband.

Devi ruled over Madurai and captured Indralok. She went on to capture Kailasha. When she saw Shiva, her 3rd breast disappeared and she realised that Shiva would be her consort.
The divine marriage was attended by all Devas and Sri Vishnu (as her brother) gave her hand to Shiva.

It is said that Indra found a swayambhu lingam at Kadamba Vanam. He placed it in Madurai where the kshetram stands. Here, Shiva is seen on the vehicle of Indra.
The Golden Lotus Tank is said to be the place where a golden lotus blossomed for the puja performed by Indra.

The Meenakshi Thirukalyanam festival is celebrated in the Chithirai month to mark the divine marriage of Meenakshi Amman. The festival includes a procession where Meenakshi and Sundareshwara travel in a chariot and Sri Vishnu gives away his sister in marriage to Shiva.

Boss is always Boss @Mitesh_Engr

Mitesh Sir's FUTURES BREAKOUT TRADES 101:

• How to pick stocks at right time?
• What to look for?
• Importance of BO post consolidation
• How to manage SL
• How to get huge profits
• Multiple Examples

In collaboration with @niki_poojary

Importance of Trading only BO or BD stocks by @Mitesh_Engr Sir: 👇

•Two questions to always ask:

~Why stock is going up/down and when?
~ Who is behind big up/down and when?

• Trade only stocks with Momentum
• Instant results
• Small SL or huge profits

Sir's take on how to Trade: 👇

• Observe fight between buyer & seller
• Position will be created within first 3 hours
• Operators will win
• Just find BO or BD
• Look for huge volume support
• Give company to operators
• ATP importance explained

How to take trade in Breakout/Breakdown stocks by @Mitesh_Engr Sir: 👇

• Check Support & Resistance
• Wait for 2-3 months consolidation
• Surge in volumes
• Trade on 3 min charts
• Small SL
• Keep trailing
• Always pyramid in profit

When and Why to Pyramid? By @Mitesh_Engr Sir

• Adding to winning positions
• Signals of continued strength
• Potentially large profits
• An Example of pyramiding in one of his trades

Some ofthe biggest breakouts occur after Volatility Contraction, the analogy is that more a spring is pressed, higher it jumps whenever it gets released.

There is a VCP Scanner on chartink (Not mine). This may also be used to find potential Breakouts.

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.