The spiritual meaning of Namaste is profound. Particularly in Hinduism, Gods are worshiped by closing the eyes and joining the palms in reverence, which indicates the recognition of their divinity.

'While paying obeisance to God, bring the palms together. After joining the hands

The thread explains my momentum scanner and how to build it in #TradePoint software.
@Definedge
Conditions :
1)EMA 8 above EMA 34 and rising
2)Candle close above previous 5 candle high
3) RSI above 60
4) Volume above previous 5 candles
5) ADX above 30
1/n

Select Double Moving Average 8 and 34
2/n

Under Patterns select Close Above Prev Bars
3/n

Qualify the candle close
4/n

RSI above 60
5/n

राम-रावण युद्ध समाप्त हो चुका था। जगत को त्रास देने वाला रावण अपने कुटुम्ब सहित नष्ट हो चुका था।श्रीराम का राज्याभिषेक हुआ और अयोध्या नरेश श्री राम के नेतृत्व में चारों दिशाओं में शन्ति थी।
अंगद को विदा करते समय राम रो पड़े थे ।हनुमान को विदा करने की शक्ति तो राम में थी ही नहीं ।

माता सीता भी हनुमान को पुत्रवत मानती थी। अत: हनुमान अयोध्या में ही रह गए ।राम दिनभर दरबार में, शासन व्यवस्था में व्यस्त रहते थे। संध्या को जब शासकीय कार्यों में छूट मिलती तो गुरु और माताओं का कुशल-मंगल पूछ अपने कक्ष में जाते थे। परंतु हनुमान जी हमेशा उनके पीछे-पीछे ही रहते थे ।

उनकी उपस्थिति में ही सारा परिवार बहुत देर तक जी भर बातें करता ।फिर भरत को ध्यान आया कि भैया-भाभी को भी एकांत मिलना चाहिए ।उर्मिला को देख भी उनके मन में हूक उठती थी कि इस पतिव्रता को भी अपने पति का सानिध्य चाहिए ।

एक दिन भरत ने हनुमान जी से कहा,"हे पवनपुत्र! सीता भाभी को राम भैया के साथ एकांत में रहने का भी अधिकार प्राप्त है ।क्या आपको उनके माथे पर सिन्दूर नहीं दिखता?इसलिए संध्या पश्चात आप राम भैया को कृप्या अकेला छोड़ दिया करें "।
ये सुनकर हनुमान आश्चर्यचकित रह गए और सीता माता के पास गए ।

माता से हनुमान ने पूछा,"माता आप अपने माथे पर सिन्दूर क्यों लगाती हैं।" यह सुनकर सीता माता बोलीं,"स्त्री अपने माथे पर सिन्दूर लगाती है तो उसके पति की आयु में वृद्धि होती है और वह स्वस्थ रहते हैं "। फिर हनुमान जी प्रभु राम के पास गए ।

10 Signs of Social Intelligence 🧠

1-Smile
2-Good posture
3-Strong eye contact
4-Fluid hand gestures
5-Let’s others talk more
6-Listens & relates
7-Comfortable Touching people
8-Walk with a swagger
9-Speaks at slower pace
10-Keeps calm under criticism

[ QUICK THREAD ]

1-Smile

How do you feel when you see someone that looks angry?

It’s a downer

No one will want to interact with you if you look pissed all of the time, it’s just negative energy

Plus, smiling is a sign of confidence and boosts others moods

2-Good posture

Don’t walk Into any social setting looking like the hunchback

It’s weak and makes you look low energy

Plus, you’re displaying low status with weak posture

Stand up straight with your chin up & chest out like a god

Walk like you’re proud of yourself

3- Strong eye contact

Ever shake someone’s hand & their eyes are either looking down or darting?

It’s weak & you probably won’t trust them

Or in conversation?

Eye contact while talking means you’re listening and paying *Attention*

Strong eye contact displays confidence

4-Fluid hand gestures

Use your hands to talk & express your points

Don’t stand there like a robot

Using the hands can make what you’re talking about exciting

It can also be used to emphasize

Exciting = positive emotion

Remember, making people FEEL is what’s important

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.