Discover and read the best of Twitter Threads about #Example
Most recents (15)
Want to see the power of Time Series forecasting in action? 📈
Let's take a look at how the retail giant Walmart uses it to improve its operations. 🤯
🧵 THREAD🧵
#timeseries #forecasting #retail #example
Let's take a look at how the retail giant Walmart uses it to improve its operations. 🤯
🧵 THREAD🧵
#timeseries #forecasting #retail #example
Walmart has been using time series forecasting for decades to predict sales and optimise inventory levels.
By analysing historical sales data, weather patterns, and other factors, they're able to make more accurate predictions about future demand for products.
By analysing historical sales data, weather patterns, and other factors, they're able to make more accurate predictions about future demand for products.
This allows them to ensure they have the right products in stock at the right time, reducing stockouts and increasing customer satisfaction.
There is one skill every professional data scientist must have, that no online course talks about 🤔
🧵↓
🧵↓
Every aspiring data scientist I talk to thinks their job starts when someone else gives them
→ a dataset, and
→ a clearly defined metric to optimize for, e.g. accuracy
They are wrong.
Things are slightly more complex in the real world.
→ a dataset, and
→ a clearly defined metric to optimize for, e.g. accuracy
They are wrong.
Things are slightly more complex in the real world.
In the real world, data science projects start from a business problem.
They are born to move a key business metric (KPI).
The data scientist's job is to translate a business problem into the *right* data science problem.
Then solve it.
They are born to move a key business metric (KPI).
The data scientist's job is to translate a business problem into the *right* data science problem.
Then solve it.
Wanna become a professional data scientist? 👩🏾🔬👨🔬
One that feels
- knowledgeable 🧠
- confident 😎
- and ready to charge well what she knows? 💰
Here is what you should do (spoiler alert, it is hard, but worth it) ↓↓↓
One that feels
- knowledgeable 🧠
- confident 😎
- and ready to charge well what she knows? 💰
Here is what you should do (spoiler alert, it is hard, but worth it) ↓↓↓
The internet is flooded with Data Science/ML content:
→ blog posts
→ newsletters
→ Twitter threads
→ Arxiv papers
→ ...
And the thing is, reading all that is not gonna get you a job.
You need to get your hands dirty ⛏️👷🏾♂️👷🏻♀️
→ blog posts
→ newsletters
→ Twitter threads
→ Arxiv papers
→ ...
And the thing is, reading all that is not gonna get you a job.
You need to get your hands dirty ⛏️👷🏾♂️👷🏻♀️
Real learning in data science (like in life) happens when you
→ face a specific problem
→ struggle to solve it, and
→ eventually solve it.
I call this the "problem-struggle-solution cycle".
This is how you learn everything in life.
And data science is not an exception.
→ face a specific problem
→ struggle to solve it, and
→ eventually solve it.
I call this the "problem-struggle-solution cycle".
This is how you learn everything in life.
And data science is not an exception.
Junior data scientists are told the problems they need to solve 👶
Senior data scientists find the problems that need to be solved 😎
Here is how they do it ↓↓↓
Senior data scientists find the problems that need to be solved 😎
Here is how they do it ↓↓↓
#Example: Imagine today is your first day at Spotify.
You are now part of the data science team responsible to maximize paid subscriptions and drive revenue.
The key question is:
"How can you increase subscription revenues with data science?" 🤔
You are now part of the data science team responsible to maximize paid subscriptions and drive revenue.
The key question is:
"How can you increase subscription revenues with data science?" 🤔
#1 Junior data scientist's idea 💡
Spotify is famous for its smart recommendations, and you completed a course on recommender systems with advanced Deep Learning techniques.
So you think:
"Let's build a better recommendation engine and increase subscriptions"
Wait a second...
Spotify is famous for its smart recommendations, and you completed a course on recommender systems with advanced Deep Learning techniques.
So you think:
"Let's build a better recommendation engine and increase subscriptions"
Wait a second...
The one skill every professional data scientist must have? 🤔
Don't look for it in online courses, it's not there.
Read the thread below and find out ↓↓↓
Don't look for it in online courses, it's not there.
Read the thread below and find out ↓↓↓
In the real world, data science projects start from a business problem.
They are born to move a key business metric (KPI):
And you, as a data scientist, need to
1 → Understand the business problem
2 → Transform the business problem into a data science problem
3 → Solve it
They are born to move a key business metric (KPI):
And you, as a data scientist, need to
1 → Understand the business problem
2 → Transform the business problem into a data science problem
3 → Solve it
To transform a business problem into *the right* data science problem you
1 → ask questions and gather business context.
2 → explore the data to find clues.
There is nothing more frustrating than building a great data science solution... to the wrong business problem.
1 → ask questions and gather business context.
2 → explore the data to find clues.
There is nothing more frustrating than building a great data science solution... to the wrong business problem.
"The best way to improve a Machine Learning model is to add more features to the input data."
You have read this sentence 100x times.
But is it true for real-world projects? 🤔 ↓↓↓
You have read this sentence 100x times.
But is it true for real-world projects? 🤔 ↓↓↓
→ It is definitely true if you are trying to win a Kaggle competition. Adding more features can only help you in this context.
→ However, if you are working on a real-world ML project, adding features is no "free lunch" 🍜
→ However, if you are working on a real-world ML project, adding features is no "free lunch" 🍜
One of the hardest problems in real-world ML projects is to prepare and send the input data the model needs to make predictions, once deployed.
aka "How to serve the input features the model needs to work well"?
aka "How to serve the input features the model needs to work well"?
How do you know if your Machine Learning model is "good enough", in a real-world project? 🤔
Let me explain ↓
Let me explain ↓
A Machine Learning model in the real world is either:
✅ Good enough. In this case, the model is deployed, its predictions are used, and add value to the business every day.
❌ Not good enough. You need to improve your model, and if that is not possible, the project is canceled
✅ Good enough. In this case, the model is deployed, its predictions are used, and add value to the business every day.
❌ Not good enough. You need to improve your model, and if that is not possible, the project is canceled
When developing a model, you use standard metrics to measure how good it is.
Examples:
→ Mean Square Error → regression problems.
→ Accuracy → classification problems.
These are the metrics you care about in Kaggle.
However, in real-world projects, these are insufficient.
Examples:
→ Mean Square Error → regression problems.
→ Accuracy → classification problems.
These are the metrics you care about in Kaggle.
However, in real-world projects, these are insufficient.
There is one skill every professional data scientist must have, that no online course talks about it 🤔
↓
↓
Every aspiring data scientist I talk to thinks their job starts when someone else gives them
→ a dataset, and
→ a clearly defined metric to optimize for, e.g. accuracy
They are wrong.
Things are slightly more complex in the real world.
→ a dataset, and
→ a clearly defined metric to optimize for, e.g. accuracy
They are wrong.
Things are slightly more complex in the real world.
In the real world, data science projects start from a business problem.
They are born to move a key business metric (KPI).
The data scientist's job is to translate a business problem into the *right* data science problem.
Then solve it.
They are born to move a key business metric (KPI).
The data scientist's job is to translate a business problem into the *right* data science problem.
Then solve it.
📢New Paper:
#Energy_sufficiency is the missing lever to tackle the ⚡️crisis & climate heating 🌡️!
With @ThPellerin we show:
1⃣ What's #sufficiency and #sufficiency_policy,
2⃣its benefits,
3⃣ #sufficiency actions in current crisis,
4⃣ what EU could do.
#Energy_sufficiency is the missing lever to tackle the ⚡️crisis & climate heating 🌡️!
With @ThPellerin we show:
1⃣ What's #sufficiency and #sufficiency_policy,
2⃣its benefits,
3⃣ #sufficiency actions in current crisis,
4⃣ what EU could do.
Simply put, energy #sufficiency is about redu-
cing energy consumption through changes
in #behaviour.
It's notion of #enough implies a social lower boundary and a ecological upper threshold.
cing energy consumption through changes
in #behaviour.
It's notion of #enough implies a social lower boundary and a ecological upper threshold.
Why do we need #sufficiency policies?
Our collective choices such as taxa-
tion, infrastructure, legal and social norms,
shape our behaviour - currently not in a sustainable way!
Also the new @IPCC_CH WGIII report proposes therefore sufficiency policies!
Our collective choices such as taxa-
tion, infrastructure, legal and social norms,
shape our behaviour - currently not in a sustainable way!
Also the new @IPCC_CH WGIII report proposes therefore sufficiency policies!
On The .50 Cent pieces, Remember the symbol on Johns Neck? …
It’s the same symbol on the Garden Sign, The Garden is where I Live, The Garden Of Eden …
I was the ONLY one out of all the Biblical ‘Ancient Of Days’ Bloodlines allowed to be in the Garden until -
It’s the same symbol on the Garden Sign, The Garden is where I Live, The Garden Of Eden …
I was the ONLY one out of all the Biblical ‘Ancient Of Days’ Bloodlines allowed to be in the Garden until -
“The War Of All Wars” ended ..
If I would have left the Garden, didn’t care what was happening in the world & didn’t do all that I have done/SHOWN to the world, NONE OF THIS WOULD HAVE WORKED !!!
WE ALL ( EVEN YOU READING THIS) have been here before, done all that we have
If I would have left the Garden, didn’t care what was happening in the world & didn’t do all that I have done/SHOWN to the world, NONE OF THIS WOULD HAVE WORKED !!!
WE ALL ( EVEN YOU READING THIS) have been here before, done all that we have
Done MANY TIMES over & over & over again trying to get it right …
So many timelines where the human race was destroyed have happened !!
This timeline was 1 of INFINITE that ACTUALLY did it !!!
What was IMPOSSIBLE became POSSIBLE because Of 1 Simple SELFLESS #ACT of Kindness!!
So many timelines where the human race was destroyed have happened !!
This timeline was 1 of INFINITE that ACTUALLY did it !!!
What was IMPOSSIBLE became POSSIBLE because Of 1 Simple SELFLESS #ACT of Kindness!!
@tabaliciouslove Everyones life is already known about.
It’s not that it’s “planned”, it’s YOU have already been here before, doing all that you have done, are doing & set out to do. The ones who have traveled have already seen & documented ALL OF IT.
EVERY SINGLE Social Media post for-
It’s not that it’s “planned”, it’s YOU have already been here before, doing all that you have done, are doing & set out to do. The ones who have traveled have already seen & documented ALL OF IT.
EVERY SINGLE Social Media post for-
@tabaliciouslove Example, these posts have already been documented into A database that has everything to do with TIME TRAVEL/Travelers ..
#Example:
This very reply, I have made TRILLIONS of times, it’s documented once I click “Reply”/Post” ..
10 years ago, if someone travels to this very-
#Example:
This very reply, I have made TRILLIONS of times, it’s documented once I click “Reply”/Post” ..
10 years ago, if someone travels to this very-
@tabaliciouslove into the future, this Day of me posting this “Reply” to YOU, this reply is saved into A Database & taken to & from the past to the present …
Every time someones would Travel, they would bring information back with them & out it into A database.
The same can be done with-
Every time someones would Travel, they would bring information back with them & out it into A database.
The same can be done with-
It’s going to be very clear why my eye was used, brace yourselves …
We’re all going to A point in life Humanity had so many chances to get to but just couldn’t/Failed every other time .. The endless loop humanity has been trapped within trying to accomplish
We’re all going to A point in life Humanity had so many chances to get to but just couldn’t/Failed every other time .. The endless loop humanity has been trapped within trying to accomplish
The “Impossible” of being set free, all it took was 1 Simple selfless act of kindness ..
I explained this A few times before, for those in the way back, I will explain again ..
WE ALL (Even you, yes you who’s reading this) has been here before) have been here before, MANY
I explained this A few times before, for those in the way back, I will explain again ..
WE ALL (Even you, yes you who’s reading this) has been here before) have been here before, MANY
MANY times over again trying to do all of this but failed every other time .. Many timelines/“Earths” have been destroyed because of not being able to come together/unite ..
All it took, that A millennia of other timelines failed to do, 1 Simple selfless act of kindness that
All it took, that A millennia of other timelines failed to do, 1 Simple selfless act of kindness that
"Charlie and I Encourage Bolt-on's and will we do many in future"- Warren Buffett. (1/5)
Let's understand what does bolt on acquisition means in this thread.
#warrenbuffett #boltonacquisiton #investing #acquistion
Let's understand what does bolt on acquisition means in this thread.
#warrenbuffett #boltonacquisiton #investing #acquistion
Let's understand what are Bolt-on Acquisition with a example, Lets take a scenario that you run a business that rents people
halls for different occasions like weddings, birthdays, Office ceremonies etc. (2/5)
halls for different occasions like weddings, birthdays, Office ceremonies etc. (2/5)
Now you have all property with you and you are doing great business but you find that every occasion like birthday and wedding involves use of food and that is where your major costs goes into.(3/5)
PPOPHET MUHAMMAD’S LAST SERMON
Prophet Muhammad (peace be upon him) delivered his last sermon (Khutbah) on the ninth of Dhul Hijjah (12th and last month of the Islamic year), 10 years after Hijrah (migration from Makkah to Madinah) in the Uranah Valley of mount Arafat.
Prophet Muhammad (peace be upon him) delivered his last sermon (Khutbah) on the ninth of Dhul Hijjah (12th and last month of the Islamic year), 10 years after Hijrah (migration from Makkah to Madinah) in the Uranah Valley of mount Arafat.
His words were quite clear and concise and were directed to the ENTIRE HUMANITY .
After praising, and thanking Allah he said:
“O People, lend me an attentive ear, for I know not whether after this year, I shall ever be amongst you again.
After praising, and thanking Allah he said:
“O People, lend me an attentive ear, for I know not whether after this year, I shall ever be amongst you again.
Therefore listen to what I am saying to you very carefully and take these words to those who could not be present here today.
O people, just as you regard this month, this day, this city as Sacred, so regard the life and property of every Muslim as a sacred trust.
O people, just as you regard this month, this day, this city as Sacred, so regard the life and property of every Muslim as a sacred trust.
001/ [article content in this tweet series 001-180 reproduced with permission from Martin Howe QC of Lawyers for Britain @lawyers4britain]
#quote "Leaving the EU on WTO terms: pulling down the barriers to world trade
Introduction: why prices will FALL after Brexit, not rise" /002
#quote "Leaving the EU on WTO terms: pulling down the barriers to world trade
Introduction: why prices will FALL after Brexit, not rise" /002
002/ #quote "Over the past couple of weeks, the media have been full of lurid scare stories about what will happen if the UK leaves the EU on WTO terms, because negotiations with the EU do not result in a withdrawal agreement." /003
#tariffs #NoDeal #Brexit #WTO #ProjectFear #shortages #food #medicines
003/ #quote "One of the most ridiculous and UNJUSTIFIED of these absurd scare stories is that it will lead to higher prices, and even shortages, of foods and medicines." /004
003/ #quote "One of the most ridiculous and UNJUSTIFIED of these absurd scare stories is that it will lead to higher prices, and even shortages, of foods and medicines." /004
