BC DATA SCIENCE
Saved by @Alex1Powell

✨✨ BIG NEWS: We are hiring!! ✨✨
Amazing Research Software Engineer / Research Data Scientist positions within the @turinghut23 group at the @turinginst, at Standard (permanent) and Junior levels 🤩

👇 Here below a thread on who we are and what we

 We are a highly diverse and interdisciplinary group of around 30 research software engineers and data scientists 😎💻 👉 https://t.co/KcSVMb89yx #RSEng
We value expertise across many domains - members of our group have backgrounds in psychology, mathematics, digital humanities, biology, astrophysics and many other areas 🧬📖🧪📈🗺️⚕️🪐
https://t.co/zjoQDGxKHq
/ @DavidBeavan @LivingwMachines
In our everyday job we turn cutting edge research into professionally usable software tools. Check out @evelgab's #LambdaDays 👩‍💻 presentation for some examples: https://t.co/GzO9m1CGz4
We create software packages to analyse data in a readable, reliable and reproducible fashion and contribute to the #opensource community, as @drsarahlgibson highlights in her contributions to @mybinderteam and @turingway: https://t.co/pRqXtFpYXq #ResearchSoftwareHour
To know more, here's a day in the life of a Research Data Scientist in our group, @louise_a_bowler ! 💯👩‍💻
https://t.co/1KPERqj7If
We are expert collaborators and work with the @turinginst community and beyond to enhance the applicability of their research. Check out the spotlights of some of our members 🙌:
https://t.co/KknkBtl6bg / @CamilaRangelS @radka_jersak @louise_a_bowler
We often host and work together with members of the civil service @faststreamuk program - see @Kevinzhangxu's thread about his experience with us earlier this year 👌: https://t.co/0UeLNhIJ9L
We highly value the development and career progression of our members: we have a dedicated Junior training role, and through our internal promotion scheme people have been promoted to Senior, Principal and even to Director! If you'd like to know more, contact @martinoreilly!
Some of our projects are covered in the Turing Podcast 🎙️, started by @EChalstrey, a (former Junior!) Research Data Scientist from the team: https://t.co/kmpPE1UldD
We work on topics ranging from data security 🔐 to air traffic control ✈️, from modelling contact-tracing during the current pandemic 😷 to the industrial revolution 🚂 (@LivingwMachines): to find out more, see our website! 👇
https://t.co/PaYng3c5Qa
Or check out our brand new @TuringDStories project!! 😻😻https://t.co/PEWnUMxoXc / @DavidBeavan @CamilaRangelS @Kevinzhangxu
And now, about you...
If you understand the importance of good practices for producing reliable software and reproducible analyses (as described for instance by @turingway), are fluent in a programming language used in #DataScience, and love to learn new skills, we strongly encourage you to apply!
In addition, if you feel that your profile would support the Group's activities, we would love to hear from you! Look at our historian turned into data scientist 👨‍💻: https://t.co/WJyc77kt49 / @f_nanni @LivingwMachines
Or at the contributions of our seismologist @kasra_hosseini to research in #digitalhumanities
https://t.co/0jPjUXvtOu
Experience in teaching and training, building #opensource communities, scientific computing and other themes are also very welcome - surprise us!
In particular, if you have worked (or would love to work!) on cloud ☁️ or high performance computing get in touch! Tomas is available if you'd like to know more 😉:
https://t.co/dgkK45JzN6 #HPC
We welcome any informal inquiries and will set up drop-in sessions if you'd like to have a chat with members of the group before applying. Just send a message to @f_nanni or @CamilaRangelS, or subscribe here:
📨 https://t.co/3e4b0dsEDJ
Again, consider applying or pass it on to colleagues and friends who might be interested!!
👉 https://t.co/LnGW7JNQX5

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Sophie Hill
Sophie Hill
@sophie_e_hill
This is a more wonky thread about how I made this visualization in #Rstats using the awesome visNetwork

First step is to create the underlying network data. We need one file of "nodes" - i.e. the people and organizations. And one file of "edges" - i.e. the connections between them.

I created these by hand, based on excellent investigate journalism:


Now we can pull these together to create a network visualization!

You'll notice that I included a column for "type" in the nodes file. This allows me to use different icons for people vs firms vs political organizations.


All the icons are taken from @fontawesome. I *think* the visNetwork 📦 currently only works with fontawesome version 4.7, which is a bit limited – e.g. I decided to use a book icon to represent the fringe Evangelical Christian sect "Exclusive Brethren"! 😂


I very much enjoyed getting to use the "incognito" icon to represent all the unknown donors that have funded Tory MP Owen Paterson's overseas jaunts!
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Data Professor
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Cheat sheet that summarizes #DataScience in 10 pages
(Links in the comments below 👇)


2/ Link to the cheatsheet by Maverick
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Goku Mohandas
Goku Mohandas
@GokuMohandas
🔥 Putting ML in Production! We're going to publicly develop @madewithml's first ML service. Here is the broad curriculum:

- 📦 Product
- 🔢 Data
- 🤖 Modeling
- 📝 Scripting
- 🛠 API
- 🚀 Production

More details (lessons, task, etc.) here: https://t.co/xmMm9XGK9j

Thread 👇


Questions that this thread will answer:

- What is it?
- Who is this course for?
- What is the format?
- What makes this course unique?
- Why constrain to open source tools?
- What are my qualifications?
- Why is this free?
- What are the

What is it?

Putting ML in Production: a guide and code-driven case study on MLOps. We will be developing and deploying Made With ML's first ML service, from Product → ML → Production, with open source tools.

This ML service will act as a foundation for all future ML features and subsequent iterations. The first feature is tagifai - multilabel classification of tags for a project. We'll discuss the need and utility of this feature in the first lesson.

Who is this course for?

- ML developers looking to become end-to-end ML developers.
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Emil Wallner
Emil Wallner
@EmilWallner
Tips for AI writers:

1. Spend 30% of your effort on skimming all student ML papers (e.g. Stanford NLP CS224n) the past 3 years and prototype your favorites

The idea is everything. Pick an area you are interested in and ideally something that has a visual aspect to it

Most of my 'on the top of my mind' ideas were bad in retrospect. Skimming 100s of student papers will give you an overview of what's interesting.

Student papers are overlooked, easy to understand, and have good compute constraints.

2. Spend 30% on your effort on coding

Create an edge to the project. Apply it to something new and use FastAI or Keras to improve the accuracy with 5-30%.

3. Spend 30% writing an in-depth article

Have a north star article in terms of structure and quality. Find something that stretches you to your utmost capability. I used @copingbear’s Style transfer article:

4. Spend 10% marketing your project

Invest a week in studying the strategies to rank on sites like HN and Reddit, then use them. If you have an interesting result and a great article, you've done the hard work.
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John Myles White
John Myles White
@johnmyleswhite
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.
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A lot of bootstrappers think they have a marketing problem:

"I need to get better at marketing."

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☝️ this is why most of my book, @marketingdevs, is about:

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"If your product is remarkable, getting noticed is a lot easier." – @peldi


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"Sales increase when you honestly evaluate what someone needs and then teach them the value of what you're selling."


To succeed, your product has to offer an outcome that is highly desirable to a large group of customers.

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Ever wonder how traders get in stocks before they explode? 🧐

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I made a thread going over exactly how I find these stocks BEFORE they take off 🚀
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Finviz!! Finviz is a free website that I use to scan for stocks.

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✅Quarter +10%
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The next scan I use is the opposite of the first one.

Simply change:
✅Quarter +10% to -10%
✅Week Down to Week up

This is my bearish scan for swing setups. 👇
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Max Fagin
Max Fagin
@MaxFagin
November is here, and that means a massive shift is coming. And by "massive" I am of course referring to the redefinition of the kilogram unit of mass that the world has been building up to for more than 100 years. Let me explain:


1/ I've had an unhealthy fascination with metrology (the study of measurement) ever since my 2nd year as a physics major when I took a class devoted to duplicating historic physics experiments, so please indulge me for going into heavy detail (get it?) about the kilogram.

2/ So what actually *defines* a unit of measurement? If you're American, you probably know a mile is 5280 feet and a foot is 12 inches and an inch is 2.54 centimeters etc. But where does this chain of definitions end? Is it turtles all the way down?

3/ It's actually not! For all units (even the imperial units used in America) the answers all end with the Système International (SI) unit definitions established and maintained for over 100 years by the Bureau International des Poids et Mesures (BIMP) in France.

4/ At the base of this tower are the SI base units. Just 7 SI base units define every other unit in existence. They are:

Kilogram, kg (mass)
Meter, m (distance)
Second, s (time)
Kelvin, K (temp)
Ampere, A (electric current)
Candela, cd (luminous intensity)
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Nikita Poojary
Nikita Poojary
@niki_poojary
Mr. Vijay Kedia built a net worth of over Rs. 800 crores.

But you probably never read past that headline.

So I binged hours of interviews to learn his investing principles and strategies.

Here are 20 lessons on investing from @VijayKedia1 Sir:

Collaborated with @AdityaTodmal


Before I start, a quick disclaimer, please don't ape his portfolio.

As the entry price, horizon and risk appetite would be far different than yours.

Rather lets draw inspiration and try to learn his stock picking skills.

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2/ Punjab Tractors:

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i. Knowledge,
ii. Courage, and
iii. Patience.
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Vibhu Vashisth
Vibhu Vashisth
@VIBHU_Tweet
Do you know?

Multiverse is mentioned in several of Hindu Scriptures.

In 1927 came a theory named 'Big Bang' which was a scientific effort to provide some explanation about how our Universe came into existence. It suggested that Universe started as a tiny, hot and dense...


...something that expanded rapidly from the singularity with a big explosion or Big Bang from which formed the galaxies, stars and the rest of the Universe.
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...Visphotak which talks about a similar theory.
The concept of Parallel universes may be novel to the modern scientists but it rests very comfortably in ancient Hindu Cosmology. The Puranas are replete with descriptions of many worlds whose inhabitants are ruled by kings in...


...the human plane and Gods in a higher plane. The many Gods in turn belong to many different worlds and planes of existence. At the highest level of hierarchy are the trinity namely Brahma, Vishnu and Mahesha, ruling the divine Kingdoms. Brahma is the creator who dreams...


...the Universe into being, which is maintained by Vishnu. What Humans perceive as reality is in fact the dream of Brahma, misled by matter. Brahman( not to be confused with Brahma) is the ground of all reality & existence. Brahman is uncreated,external, infinite & all-embracing.
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