#SAREGAMA I gave bearish view near 5200 and chart says we may see reversal near 3500. Good level to accumulate https://t.co/xh3jmmxfWI

8 March 1679 - The date on which 300 saffron clad warriors gave their life to protect temples from mugal army. Thread➡️
Aurangzeb's huge army, which was adorned with artillery, elephant and horses, under the leadership of Commander Darab Khan had marched to punish the ruler of/1

Khandela Raja Bahadur Singh, who became a rebel due to the anti-Hindu policies of Aurangzeb, and to destroy the temples of Shekhawati. Bahadur Singh to compete with such a large army, vacated Khandela for the purpose of conducting guerilla warfare and went Kot Sakrai /2

located in the inaccessible hills of Sakrai. People of Khandela also vacated Khandela and hid in nearby villages.

But some Shekhawat warriors did not like this as they knew that the royal army would not leave a single temple located in Shekhawati unbroken./3

so soon the teams of self-sacrificing Dharma-protectors Shekhawat heroes started reaching Khandela to protect the Dev temples.

Sujan Singh Shekhawat, the young thakur of Chhapoli, was coming back from his wedding when he heard about the imperial army from Shepherds./4

झिरमीर झिरमिर मेहा बरसे,मोरां छतरी छाई |
कुल में है तो आव सुजाण, फोज देवरे आई ||

if you are born in your glorious clan, then come, the army have come to destroy temple. /5

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.

Want to do an MBA for free ?

A thread 👇

1) Leadership: Foundations of Teamwork and Leadership

School: wharton

2) Marketing: Marketing Management

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3) Microeconomics: Microeconomics for Managers

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4) Financial Theory

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The chorus of this song uses the shlokas taken from Sundarkand of Ramayana.

It is a series of Sanskrit shlokas recited by Jambavant to Hanuman to remind Him of his true potential.

1. धीवर प्रसार शौर्य भरा: The brave persevering one, your bravery is taking you forward.

2. उतसारा स्थिरा घम्भीरा: The one who is leaping higher and higher, who is firm and stable and seriously determined.

3. ुग्रामा असामा शौर्या भावा: He is strong, and without an equal in the ability/mentality to fight

4. रौद्रमा नवा भीतिर्मा: His anger will cause new fears in his foes.

5.विजिटरीपुरु धीरधारा, कलोथरा शिखरा कठोरा: This is a complex expression seen only in Indic language poetry. The poet is stating that Shivudu is experiencing the intensity of climbing a tough peak, and likening

it to the feeling in a hard battle, when you see your enemy defeated, and blood flowing like a rivulet. This is classical Veera rasa.

6.कुलकु थारथिलीथा गम्भीरा, जाया विराट वीरा: His rough body itself is like a sharp weapon (because he is determined to win). Hail this complete

hero of the world.

7.विलयगागनथाला भिकारा, गरज्जद्धरा गारा: The hero is destructive in the air/sky as well (because he can leap at an enemy from a great height). He can defeat the enemy (simply) with his fearsome roar of war.

Can we control the output of neural generation systems?
Can we build a better chatbot using this control?
And what makes a good conversation anyway?

Check out the blog post for our NAACL paper:

https://t.co/UAAUxSeA0L

#AI #NLProc #DeepLearning #ConversationalAI @facebookai

This post got a little delayed since the paper's publication, but the intervening time has given me an opportunity to reflect.

So this post has some extra thoughts regarding more recent NLG developments - e.g., pretrained models like GPT(2), and the suitability of beam search.