#CDSL -1305

After almost attained 4.618%
Correction likely retracement level shown in chart.

#Possibility

Best resort on the Ganga at Rishikesh

AGAMA SHASTRA:THE SCIENCE BEHIND THE MARVELS OF HINDU ARCHITECTURE

Agama Shastra is a Sanskrit word that means the manual for worship, temple building, rituals etc in Hindu Tradition.From Sanskrit,agama means handed down by tradition and Shastra means a commentary or treatise.

Therefore, Agama Shastra is a collection of ideas that drafts the rules for worship, temple construction, spirituality and rituals. It has been a guideline for many Hindus from ancient times. It's a collection of Sanskrit, Tamil and Grantha scriptures that mostly contains...

...methods of temple construction, idol creation, philosophical doctrines and meditative practices. It came into being after years of assimiliation and from a variety of sources. Some parts of it are pre-vedic while some are post-vedic.

Hindu Temples are not just temples, they are the pride and identity of Hindus. They are the symbols of Hindu unity and their religious aspirations. Temples are the places of spiritual healing and are our connection with the creator almighty.

Temples are the priceless treasure of our History, Heritage ,Art & Architecture. Architecture that mesmerises and spell bounds you. And Agama Shastra is that very text which is responsible for such a mesmerising and spell binding quality and beauty of our Hindu Temples.

You want to buy a house.

You take a loan from the bank.

The bank asks you, “what if you don’t pay back?”

You say, “take my home and sell it”.

(Thread)

That makes sense. The bank gives you a loan and in case you don’t pay, the bank will take over your house and sell it and recover its money.

That’s collateral.

Banks also lend money to big corporations. With them, banks don’t always have collateral.

So a loan where the bank has collateral is considered safer for the bank.

In the early 2000s, the banks in the USA were giving out loans to people for buying houses.

The economy had just recovered from the tech bubble in 2000 where many banks had given out loans to businesses that had shut down.

In that backdrop, the banks found giving home loans safer.

Starting my 2nd thread on Sringeri Parampara. This will cover the Jagadgurus after Sri Vidyaranya to Sri Shivabhinava Nrisimha Bharati.

It is really very tough to match the brilliance and achievements of Vidyaranya. After whom came 15 - Chandrashekara Bharati [1386-1389].

The next Acharya was Nrisimha Bharati [1389-1408]. Harihara raya found a town for this Acharya - Narasimhapuram. Acharya helped the king by guiding him in political affairs. He also initiated the kind with mahamantras for spiritual development.

Subsequent Acharyas were
15-Puroshottama Bharati [1408 - 1448]
16-Shankara Bharati[1448 - 1455]
17-Chandrasekhara Bharati II [1455 - 1464]
18- Nrisimha Bharati II [1464 - 1479]
19-Puroshottama Bharati II [1479 - 1517]

20-Ramachandra Bharati [1517 - 1560]. Sadashiva Raya was emporer of Vijayanagara during this time.
21-Nrisimha Bharati III [1560 - 1573]
22-Nrisimha Bharati IV [1573 - 1576]
23-Nrisimha Bharati V [1576 - 1600]

24-Abhinava Nrisimha Bharati [1600-1623]. When he visited Malahanikareswara temple for first time he noticed there was no Vinayaka there so he took piece of turmeric and drew outline of Ganesha on a pillar and offered puja.

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.