There has been speculation that changes to the way the internet is implemented will be rolled out to allow access only to authorized sites.

Some think this is impossible

I'm here to tell you it is not, and very likely.

Allowing access only to white listed IP addresses is easy.

Prasanna Venkatesa Perumal #temple -Gunaseelam,Near Trichy,TN #Thread

Gunaseela Mahatmyam,a chapter of Bhavishyottara Purana describes greatness of this place.

Venkatachlapathi of Tirumala Tirupati appeared b4 Gunaseela Rishi here,so Gunaseelam is known as Ten(South)Tirupati

Prasanna Venkatesa Perumal is in a standing posture with 4 arms holding sankha & chakra in the upper hands.The lower right hand is in abhaya pose,blessing devotees &left hand is in kati hasta,resting on waist.

A sceptre(senkkol)rests on right shoulder,with which this murti is believed to cure people affected by mental illness.These patient stay here for a period-48 days& participate in poojas&most of them get relieved of their problems.There is a temple run Mental Rehabilitation center

#storytimethread -As per Sthala Puranam,existence of this temple is due to efforts of Gunaseela Rishi, a disciple of Thalpiya Maharishi.
Thalpiya Maharishi along with his disciple Gunaseela Rishi once went to Himalayas.On his way back, Gunaseela Rishi stayed back at Tirupathi.

He was so wanted to have darshan of Venkatachalapathy in Gunaseelam near his asharam & bless the devotees.

He came back, bathed in the Cauvery,took blessing from his guru &undertook severe penance here in his ashram in Gunaseelam.

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.

My System for momentum trading🧵:

1. Stock Identification:

Daily and Weekly Delivery Analysis using @mystockedge
Theme Confirmation using Internet and Network

2. Stock Confirmation:

Relative Strength of a stock visavis market using RS55 model listed in @mystockedge

1/n

3. Stock Participation:

Only when chart showing short term breakout along with RS55>0 and RSI>50. I am ready to leave some initial movements.

4. Position buildup:

Every time the stock gives a breakout from the previous swing high add more position and go all-in.

2/n

5. Stock Exit:

I run two portfolios: Short term Swing and Long term Swing.

For Exit in Short term swings, I use a 2hourly Chart with super trend and RS. I am using @tradingview for the same.

For long term swing, I exit when the RS of the stock goes below 0. Period.

n/n

In 1937, a trucker got frustrated waiting for his cargo to be unloaded. He later sold his company for $1.1 billion.

Here’s the story of how Malcom McLean made a billion dollars and which startup could be following in his footsteps. (Inspired by our episode with @laurabehrenswu)

In the early 1950s, the shipping industry was a dying business.

New York’s docks were handling half as much domestic cargo in the early 1950s as they had been in the depressed 1930s.

In thirty years, no one had invested significant money in coastal shipping.

Why?

As McLean found out, loading ships was difficult and slow.

A truck or train would deliver items to the port. Each item was unloaded separately, recorded, and carried to storage.

When a ship was ready, each item was taken from storage, counted again, and hauled on-board.

The cost of this labor was significant. As one expert at the time explained:

“A four-thousand-mile voyage for a shipment might consume 50 percent of its costs in covering just the two ten-mile movements through two ports.”

Yet, despite the industry’s issues, it felt little pressure to change.

Foreigners were barred from operating domestically. Cartels ran international routes. And gov. subsidies eased the pain of labor costs.

Reshaping the industry needed an outsider.

Enter Malcolm McLean.