There are many ways to trade and invest in the stock market. In my experience, buying and holding can take advantage of a big move, but it has a number of disadvantages over a nimble approach. To compound and avoid large drawdowns, big consistent returns require turnover.

Here is my Thread on 'Ketu (South Node) Through Nakshatras' The 27 Constellations 🙏❣.

Do check your “Past life Mastery” which KETU Represents🤞🏻.

1. Ketu in Ashwini Nakshatra:

Here native is Great at Financial Planning, Face reading, understanding other’s mind and intention, Driving Fast they don’t like but they are wayyy smooth over driving Fast. This is also great position which can make native Great Surgeon,

Neurologist, Psychologist.
These natives are Selfless and Sacrifice self for others. They gets Fame and Success but they just don’t care.

2. Ketu in Bharani Nakshatra:

They are good at Flirting, Attracting opposite sex, studing ancient subjects. They are also Great at Creativity and Artistic activities. The are lazy but they are really open minded who handles situations really well.

In Past life they have handles many things which is now helping them to make things easier in this life. They are great Leaders too.

They are really good at Hard work and Smart work both. And yes just as Ashwini they don’t much care about Fame and Success!

1/ Throughout my startup career, I’ve seen many founders have an aversion to sales. This is a mistake that can kill your startup.

2/ Sales is often viewed as either a saving grace or proof that the product isn’t good enough (because it should sell itself). Neither are ever true. Some common mistakes that result in...

3/ Mistake 1: Hire a sales rep before reaching product/market fit to get your initial batch of customers. This is a mistake because founders need to work through their MVP with early adopters to truly understand what it is they’re selling.

4/ Mistake 2: Reach product/market fit, need to scale, and rely entirely on self-serve. For enterprise products that require big commitments and internal shifts, almost no product is self-explanatory enough to sell itself.

5/ Mistake 3: Make a first sales hire who isn’t scrappy enough to help mold the sales process from scratch. Some salespeople are amazing at their jobs, but not cut out to establish the processes that others end up following. This skillset is what @rdedatta calls a “sales ninja”.

Yoga Ramar Temple
#Nedungunam
#TamilNaduTemples 🚩

Yoga Ramar Temple is located near Thiruvannamalai. Shri Rama is seated with eyes closed, without any weapons. Mata Sita  pointing to the feet of Rama telling that  everyone is safe at his feet. Lakshmana standing near Shri Rama

Hanuman is seen chanting Vedas obediently sitting before Shri Rama.

Sthala Puranam says that, Sukabrahma Maharishi had been doing Tapasya here, for the darshan of Sri Rama. Prabhu Shri Ram, pleased with his tapasya, came here after Rama Ravana yudham. Since Rama was returning

after the war, he did not have any weapons with him.

Another gopuram called Kili Gopuram is there for Sukabrahma Maharishi. There is a hill nearby called Dheergachala. According to Sthala puranam, Sri Padham of Prabhu Rama are found on the top of the hill

It is said that this is the place where Shri Rama gave darshan to Suka Maharishi. Nedumgunam means which shows all qualities of Shri Rama who is Maryadha purushottam. Shri Ramanavami is very famous here.

Jai Sri Ram
🙏🕉🙏

This post is pretty bizarre, but it manages to hit on so many false beliefs that I've seen hurt junior data scientists that it deserves some explicit

(1) The notion that R is well-suited to "building web applications" seems totally out of left field. I don't feel like most R loyalists think this is a good idea, but it's worth calling out that no normal company will be glad you wrote your entire web app in R.

(2) It is true that Python had some issues historically with the 2-to-3 transition, but it's not such a big deal these days. On the flip side, I have found interesting R code that doesn't run in modern R interpreters because of changes in core operations (e.g. assignment syntax).

(3) "Most of the time we only need a latest, working interpreter with the latest packages to run the code" -- this is where things get real and reveal some things that hurt data scientists. If this sentence is true, it's likely because you don't share code with coworkers.

(3) Really is a broader issue in data science: people only think of what they need to do their work if no one else existed and code was never maintained. Junior data scientists almost always operate on projects they start from scratch and don't have to maintain for long.