#INFOSYS

Time to be alert on this one on long side

Cmp 1875, expecting wave C move down towards 1600 in coming days

View negates above 1954 previous top

1) Core attributes of a promising founder worth following:
- Progress/trajectory over time
- How well they lead a team &
- Make the vision happen
- Most impressed when someone is way ahead of where you thought they would be when you check up/see them a few months later.

2) Indie Makers have such a benefit of being small, fast, nimble workers in comparison to big companies.

We can easily pivot and vastly change a project of ours. We can change as we learn more about our users.

Big companies can take months/years for even the smallest of pivots.

3) Before you find a product market you can pivot your project as many times as necessary until you find something that works.

Then you only have one thing to do: scale, scale, scale.

4) Be obsessed with the little details.
- listen to every single person who uses your product
- reply to every single person who emails you about your product
- ask them what they like and do not like
- iterate your product, make changes, pivot if necessary

5) Paul Graham's (@paulg) name came up with a feeling of great admiration! Naturally! It was Paul who said:

In the early stages of a company just;
- write code
- talk/sell to customers to stress test your idea

Nothing else.

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.

The Story of how Mary Slessor Stopped the killing of Twins but sadly died of Fever.

All you need to know

Retweet to educate someone

Killing new-born twins was common practice in the 19th century among the Ibibio people of Nigeria, but one Scotswoman went to great lengths to put an end to this.

Aberdeen-born Mary Slessor was one of the few missionaries in Africa who learnt the local language, adapted to the native customs and environment and gained the trust of the locals in order to make a truly positive impact.

Her father, a shoe-maker from Buchan, became incapacitated by alcoholism and Mary more or less became the breadwinner for the family.

From the age of 11, she worked as a ‘half-timer’ mill girl in the Baxter Brothers and Co Ltd, spending half the day at a school provided by the mill owners and the other half working for the company