Saw a few of you discussing govt. corruption on my TL.
My daddy is a babujeet he regularly tells me story of corruption of fellow babus, would like to share a few instances here.
Would delete this thread in 12 hours, taking a big risk.

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

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”.

SRI KANTESH HANUMANTHA, KADARAMANDALAGI (KAR)
#bharatmandir

KANTESHA means Prabhu full of brightness.
Here, Sri Hanuman appears with a front face and sparkling eyes. Earlier, the village was also called KANTESHPURI on the name of Kantesha Hanuman.

Several thousands of years ago, Hanuman lived in this village. He once saw the Sun and mistaking it to be a fruit, began flying towards it. Since then, this village came to be known as Kadara Man Dalagi. (Kadar means rays, mandala is cluster of rays).

It is believed that King Janmejaya had set up the shrine to get rid of his difficulties.
There is a small pond on the right side of the kshetram where Teppotsava (Float festival) is celebrated.

Kanaka Dasa has praised Sri Kantesha in his various poetic compositions.

Kanaka Dasa was the first devotee to popularize the power of Kantesha. It is said that once Kanaka Dasa was deeply wounded in a battle. To seek blessings, he visited Tirupati but Sri Venkatesha appeared in his dream and advised him to see Kantesha first before seeing him.

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.