#mcdowells 🍻

Attractive chart setup.
Descending channel & Supply zone breakout and retest.

#Nifty #stock #trading #invest #StockToWatch #stockmarket

1/ The first 18 months of starting a company is often life or death. I must've made 5 different companies that each failed within 9 mo. 😭 Each time the company failed I figured out what I could do better. Eventually startup #6 got to $40K/mo by month 18. Here’s what I learned...

2/ Stay focused! Ignore things that are a waste of time: meetups & conferences, meetings with no clear agenda, fundraising if you're not fundraising, reading lots of tech media articles, etc. Every week should feel like significant progress in the first year.

3/ Your first 5 hires will be the difference between life or death. Choose carefully. Be picky. Many of the things we do at the company still are a result of those early hires' legacy. Have fun as a tight knit team. It will change & evolve as you get bigger so enjoy this moment.

4/ Growth may be flat for the first 9 months. It's gonna be okay. Almost every company has experienced this: Airbnb had to sell cereal in-between, Slack failed as a gaming company first, Tesla sold only 147 cars after 6 years! You probably won't be an overnight success either.

5/ In the beginning, do customer support yourself. You will learn a lot about why your product sucks. I did 5,000+ support tickets when it was the two of us. Delight customers & fix things fast while you learn. It will help you build an amazing intuition about your customers.

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.

Thats a gg, Satan

Black movie goers know which movies are for us and which films aren’t. We really don’t like our stories being made into films that center (and humanize) people that hate us. The filmmakers/studio know that by naming the film “The Green Book”, black movie goers...

...are going to be expecting a story about black people trying to safely navigate the country (real history) and instead will get a white savior film. Like folks went to see Detroit thinking it was about the riots...

Anywhoo, I know Mahershela is fantastic in it. He was the best thing about the trailer. As rich as the history behind the creation of ‘The Green Book’ is/was, as amazing as Dr. Don Shirley’s story is, WHY is this film about a random, racist driver and his family?

This feeds into the ignorant anti-Black American stereotype of “Black Americans don’t have any culture/history/mythology” or whatever. That our stories are still both being used while simultaneously erased in 2018 is wild to me. It’s gonna clean up come award season. 🤦🏾‍♀️

And now, if black filmmakers WANTED to make a film about The Greenbook, guess what it can’t be called🙃. Just like if someone wanted to make a film about the actual Detroit riots, guess what it can’t be called? Then those filmmakers would run into...

Saptapadi

The most essential rite (Sanskrit: rītī) of a Hindu marriage ceremony is Saptapadi (English: seven steps, saptapadī). Saptapadi is a Sanskrit term that means "seven steps." The wedded couple walks seven steps after tying the Mangalsutra, which is known as Saptapadi.

The couple legally becomes husband and wife after the seventh step.
Hindu wedding rituals: During Saath Phere, the bride and groom exchange their marital vows while circumambulating (walking around) the sacred fire seven times.

This is because the bride and groom exchange marriage vows and hope for a happy married life together.

1. The first marriage vow, out of seven, is a petition to the Lord for nutrition and nourishment for the Hindu bride and groom.

2. Hindu Bride and Groom: The second marriage promise is for strength in sickness, health, good times, and terrible times.

3. For the Hindu Bride and Groom - The third marriage promise is for the Hindu bride and groom's prosperity.

4. For Hindu Bride and Groom - The fourth pledge is to stand by their families in good times and bad.