The MOST overlooked skill in data science...

And it could get you a $20,000 promotion.

Here's how. 🧵

#datascience #stats #rstats

Text analysis is a treasure trove of predictive information.

Yet 90% of companies don’t know how to use it.

They are overlooking one of the most powerful and predictive sources of information…
In fact, text analysis is part of the strategy that I used to help double my business in 2022...

While companies like Facebook (Meta) lost 70% of their value.

My company went from $0.9M/year to $2,000,000 per year.

Using text analysis was a key piece.
So imagine how valuable you could become to your company if you doubled the part of the business you touch...

In less than 12 months.

They'd be more than happy to give you a $20,000 raise...

You just made them $1M. (or more)
But you need to learn Text Analysis so you can improve model performance...

Which leads to:

1. a better understanding of customers

2. a better understanding of products

3. better lead scoring

4. better marketing

5. $1,000,000+ ROI
Learning text analysis is full of pitfalls...

Yeah, there's a ton of text data available.

But which do you use?
The mistake every data scientist makes is trying to use every source of data...

And they always go for unstructured text first.

Big mistake.
The structured data is actually EASIER and MORE VALUABLE.

So start there.
Now you're probably thinking, great idea! But how?

How 'bout I show you...
I'd like to help you learn Text Analysis for free.

I put together a FREE workshop where I'll uncover how I do text analysis.

Here's what you learn:
1. How to work with text data

Learn how to tokenize structured and unstructured text so you can make it useful for solving business problems
2. My simple technique for automating text data mining

It's 1/10th of the code versus how the way I'm seeing others do it
3. How to improve your model performance with text data

Get the insider's secret to model performance increase + make your company more profitable
4. Get ideas for your future job portfolio

Expand your data science tool chest with Text Analysis
What's Your Next Step?

My Text Analysis Workshop is completely free.

All you need to do is register & show up.

https://t.co/cA1nVZhVY3

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We have shortlisted these ebooks every no-code learner should read:

#1 The No-code Revolution

https://t.co/reOSvnTOs6

The ebook from @webflow will provide an overview of the no-code movement and its importance.

It also provides insights on bringing no-code to your company and how it will impact the world!

#2 Zero to MVP with No-code

https://t.co/7JD6RQvocZ

The book written by @MakadiaHarsh, with 21 chapters, provides a complete guide to building no-code apps.

It also explains the difference between no-code, code, & low-code, and 120+ tools to build MVPs.

#3 The What's, How's, and Why's of No-code

https://t.co/YH5L6pJrW0

This book from @QuixyOfficial provides insights on no-code development, how it's different from other development, and why it is essential for stakeholders of an organization.

#4 No-code Ebook

https://t.co/PV6M9oMZCF

The book developed by @NeotaLogic explains the importance of no-code and provides advice on selecting the correct no-code platforms according to requirements.
Trading Strategies 101

14 "must-try" trading strategies you can start using today: 🧵

Collaborated with @niki_poojary

We'll break these into portions of:

1. Intraday Trading Techniques
2. Positional Trading Techniques
3. Indicator Applications

1/ 6 Intraday Strategies 🧵

How to Filter Stocks for Intraday


2/ Intraday BNF strangle based on OI data. 🧵


3/ A few setups to make intraday trading easy.

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Recently, the @CNIL issued a decision regarding the GDPR compliance of an unknown French adtech company named "Vectaury". It may seem like small fry, but the decision has potential wide-ranging impacts for Google, the IAB framework, and today's adtech. It's thread time! 👇

It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details):
https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha

I've read it so you needn't!

Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.

The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.

Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.
I'm going to do two history threads on Ethiopia, one on its ancient history, one on its modern story (1800 to today). 🇪🇹

I'll begin with the ancient history ... and it goes way back. Because modern humans - and before that, the ancestors of humans - almost certainly originated in Ethiopia. 🇪🇹 (sub-thread):


The first likely historical reference to Ethiopia is ancient Egyptian records of trade expeditions to the "Land of Punt" in search of gold, ebony, ivory, incense, and wild animals, starting in c 2500 BC 🇪🇹


Ethiopians themselves believe that the Queen of Sheba, who visited Israel's King Solomon in the Bible (c 950 BC), came from Ethiopia (not Yemen, as others believe). Here she is meeting Solomon in a stain-glassed window in Addis Ababa's Holy Trinity Church. 🇪🇹


References to the Queen of Sheba are everywhere in Ethiopia. The national airline's frequent flier miles are even called "ShebaMiles". 🇪🇹