Do you love 3D maps, worlds & visualisations? Here are 24 world creators, mapmakers, or visuals I've come across recently. Brilliant and creative minds using many different tools! PART 1 #dataviz #GISchat #3dmaps #map #gis #3d 1/🧵

Steven Kay | @stevefaeembra creates many original and cool #3dmaps such as this great visualisation of Windturbines in the British Isles. Follow him! #Blender3D and #QGis are his tools. #SDGs #Wind #b3d 2/🧵

I'd like to thank Rafael Nicolas Fermin Cota for pointing me to this modified graphic from a recent Harvard Business Review article on "Prioritizing Which Data Skills Your Company Needs".

You hear Harvard Business Review, & you think this must be legit.

Well, in this case, they dropped the ball.

If you're coming up with an educational plan for your org in 2022, here are some tips...

Well, in this case, they dropped the ball.

If you're coming up with an educational plan for your org in 2022, here are some tips...

(1/3) Evaluate models performance with metrica 🚀🚀🚀

Metrica is a new R package that provides functions and tools for quantifying and visualizing models performance 🧵 👇🏼

#rstats #stats #dataviz #machinelearning #OpenSource

Metrica is a new R package that provides functions and tools for quantifying and visualizing models performance 🧵 👇🏼

#rstats #stats #dataviz #machinelearning #OpenSource

(2/3) It supports regression, classification, machine learning, and forecasting models using a variety of evaluation metrics such as goodness of fit, confusion matrix, regression plots, and providing custom plots using ggplot2 🌈.

(3/3) Getting started 👇🏼

install.packages("metrica")

License: MIT 🦄

Resources 📚

Documentation: adriancorrendo.github.io/metrica/index.…

Source code: github.com/adriancorrendo…

Big shout out to Adrian Alejandro Correndo and the rest of the package authors! 🙏🏼

install.packages("metrica")

License: MIT 🦄

Resources 📚

Documentation: adriancorrendo.github.io/metrica/index.…

Source code: github.com/adriancorrendo…

Big shout out to Adrian Alejandro Correndo and the rest of the package authors! 🙏🏼

If you are looking for a great introduction to unsupervised learning, I recommend checking @DeepMind introduction to unsupervised learning tutorial 🧵👇🏼

#stats #python #machinelearning #ml #OpenSource

#stats #python #machinelearning #ml #OpenSource

The tutorial fucoses the foundation of unsupervised learning with Python, covering both Probabilistic Models and Neural Networks methods 🌈.

#NeuralNetworks

#NeuralNetworks

1/ "Software is eating the world. Machine learning is eating software. Transformers are eating machine learning."

Let's understand what these Transformers are all about

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataAnalytics

Let's understand what these Transformers are all about

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataAnalytics

2/ #Transformers architecture follows Encoder and Decoder structure.

The encoder receives input sequence and creates intermediate representation by applying embedding and attention mechanism.

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI

The encoder receives input sequence and creates intermediate representation by applying embedding and attention mechanism.

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI

3/ Then, this intermediate representation or hidden state will pass through the decoder, and the decoder starts generating an output sequence.

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataScientist #DataAnalytics #Statistics

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataScientist #DataAnalytics #Statistics

1/ When it is important to standardize variables in #DataScience #MachineLearning ? - A Thread

#DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataScientist #DataAnalytics #Statistics #programming #ArtificialIntelligence #Data #Stats #Database #BigData #100DaysOfCode

#DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataScientist #DataAnalytics #Statistics #programming #ArtificialIntelligence #Data #Stats #Database #BigData #100DaysOfCode

2/ It is important to standardize variables before running Cluster Analysis. It is because cluster analysis techniques depend on the concept of measuring the distance between the different observations we're trying to cluster.

#DataScience #MachineLearning #DeepLearning

#DataScience #MachineLearning #DeepLearning

3/ If a variable is measured at a higher scale than the other variables, then whatever measure we use will be overly influenced by that variable.

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataScientist #DataAnalytics #Statistics

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataScientist #DataAnalytics #Statistics

1/ Can you classify something without seeing it before - that's what Zero-Shot Learning is all about - A Thread

👉 One of the popular methods for zero-shot learning is Natural Language Inference (NLI).

#DataScience #DeepLearning #MachineLearning #100DaysOfMLCode #Pytho

👉 One of the popular methods for zero-shot learning is Natural Language Inference (NLI).

#DataScience #DeepLearning #MachineLearning #100DaysOfMLCode #Pytho

2/ Zero-shot learning is when we test a model on a task for which it hasn't been trained.

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats #DeepLearning #100DaysOfCode #Database #BigData

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats #DeepLearning #100DaysOfCode #Database #BigData

3/ In Zero-shot classification, we ask the model to classify a sentence to one of the classes (label) that the model hasn't seen during training.

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI

1/ Why do we need the bias term in ML algorithms such as linear regression and neural networks ? - A thread

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats #DeepLearning #100DaysOfCode

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats #DeepLearning #100DaysOfCode

2/ In linear regression, without the bias term your solution has to go through the origin. That is, when all of your features are zero, your predicted value would also have to be zero.

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming

3/ However that may not be the attributes of the training dataset.

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats #DeepLearning #100DaysOfCode #Database #BigData #DataAnalytics

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats #DeepLearning #100DaysOfCode #Database #BigData #DataAnalytics

1/ #MachineLearning #Interview questsion -

Why L1 regularizations causes parameter sparsity whereas L2 regularization does not?

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats

Why L1 regularizations causes parameter sparsity whereas L2 regularization does not?

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats

2/ L1 & L2 regularization add constraints to the optimization problem. The curve H0 is the hypothesis. The solution to this system is the set of points where the H0 meets the constraints.

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming

3/ Regularizations in statistics or in the field of machine learning is used to include some extra information in order to solve a problem in a better way.

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data

Dalot vs Wan bissaka

Which is better in stats PER 90???

--------------------------------------------

Let's start with passes we see that dalot and wan bissaka in passes per 90 they have many similarities,but the assist statistic and key passes is axtual very bad...

Which is better in stats PER 90???

--------------------------------------------

Let's start with passes we see that dalot and wan bissaka in passes per 90 they have many similarities,but the assist statistic and key passes is axtual very bad...

Z-Scores are a great #Stats tool to help give us some insight into a data set, especially in the #Bitcoin and On-Chain world.

So, what exactly is a Z-Score? What is it good for? What are its limitations? What kinds of Z-Scores are there?

Let's dive in.👇🧵

So, what exactly is a Z-Score? What is it good for? What are its limitations? What kinds of Z-Scores are there?

Let's dive in.👇🧵

Petit thread sur l'usage des intervalles de confiance dans les sondages politiques. Ici en utilisant le dernier sondage en rolling de l'IFOP pour les présidentielles françaises 👇

#Presidentielle2022 #Sondage #stats

#Presidentielle2022 #Sondage #stats

La présentation de ce sondage inclue une notice méthodologique avec un intervalle de confiance générique à utiliser. Celui-ci est exact, même s'il faut faire l'impasse sur la méthode de quota utilisée ici.

Mais il ne contient pas les intervalles de confiance pour chaque résultat. J'ai cherché à les ajouter à partir des données fournies leur notice méthodologique et les conclusions sont assez différentes. Première conclusion : ce n'est pas facile...

🚨Job talk thread🚨

Title: What Can *Conformal Inference* Offer to Statistics?

Slides: lihualei71.github.io/Job_Talk_Lihua…

Main points:

(1) Conformal Inference can be made applicable in many #stats problems

(2) There are lots of misconceptions about Conformal Inference

(3) Try it!

1/n

Title: What Can *Conformal Inference* Offer to Statistics?

Slides: lihualei71.github.io/Job_Talk_Lihua…

Main points:

(1) Conformal Inference can be made applicable in many #stats problems

(2) There are lots of misconceptions about Conformal Inference

(3) Try it!

1/n

Conformal Inference was designed for generating prediction intervals with guaranteed coverage in standard #ML problems.

Nevertheless, it can be modified to be applicable in

✔️Causal inference

✔️Survival analysis

✔️Election night model

✔️Outlier detection

✔️Risk calibration

2/n

Nevertheless, it can be modified to be applicable in

✔️Causal inference

✔️Survival analysis

✔️Election night model

✔️Outlier detection

✔️Risk calibration

2/n

1/ Continuons notre série "où est passé l'argent de la recherche" avec les études du #SARS_CoV_2 dans les #eaux usées.

Sur le principe, pourquoi pas ?

C'est assez robuste pour y retrouver les #drogues. En France, ces travaux du @CNRS étaient dans @libe

liberation.fr/societe/2013/0…

Sur le principe, pourquoi pas ?

C'est assez robuste pour y retrouver les #drogues. En France, ces travaux du @CNRS étaient dans @libe

liberation.fr/societe/2013/0…

2/ Le soucis est qu'un #virus c'est pas une molécule.

La bonne nouvelle a été que l'on peut détecter le #SARS_CoV_2 dans les eaux usées !

La moins bonne a été qu'il était difficile de savoir quoi en faire...

Car savoir qu'un virus pandémique circule aide peu.

La bonne nouvelle a été que l'on peut détecter le #SARS_CoV_2 dans les eaux usées !

La moins bonne a été qu'il était difficile de savoir quoi en faire...

Car savoir qu'un virus pandémique circule aide peu.

3/ Au niveau du #dépistage, à peu près aucune étude sur les #eaux usées n'a regardé la #sensibilité ou #spécificité de la méthode.

Quelle variabilité pour un même échantillon ?

Quelle variabilité pour des échantillons pris le même jour à une même station ?

Quelle variabilité pour un même échantillon ?

Quelle variabilité pour des échantillons pris le même jour à une même station ?

Geographic Data Science with R! 🚀🚀🚀

The R for geographic data science, by @maps4thought, provides an introduction to data science with applications for geographic data. 🧵👇

Images credit: from the book

#rstats #DataScientists #MachineLearning #Stats

The R for geographic data science, by @maps4thought, provides an introduction to data science with applications for geographic data. 🧵👇

Images credit: from the book

#rstats #DataScientists #MachineLearning #Stats

The book follows the syllabus of the "R for Data Science" course at the School of Geography, @uniofleicester. The book is still a work in progress, and a draft version is available online.

Bayesian Generalized Linear Models with Julia! 🚀🚀🚀

TuringGLM is a new Julia package for GLM models with Bayesian flavor ❤️. As its name implies, the package uses the Turing package on the backend for the regression engine. 🧵 👇🏼

#JuliaLang #TuringLang #DataScience #Stats

TuringGLM is a new Julia package for GLM models with Bayesian flavor ❤️. As its name implies, the package uses the Turing package on the backend for the regression engine. 🧵 👇🏼

#JuliaLang #TuringLang #DataScience #Stats

New book for Bayesian statistics with #Python! 📚📊🚀

The Bayesian Modeling and Computation in Python by

@aloctavodia, @canyon289, and @junpenglao provides an introduction to Bayesian statistics using core Python libraries for Bayesian 🧵 👇🏼

#bayesian #MachineLearning #stats

The Bayesian Modeling and Computation in Python by

@aloctavodia, @canyon289, and @junpenglao provides an introduction to Bayesian statistics using core Python libraries for Bayesian 🧵 👇🏼

#bayesian #MachineLearning #stats

The book covers the following four topics:

- Bayesian Inference concepts

- Bayesian regression methods for linear regressions, splines,

- Time series #forecasting

- Bayesian additive regression trees

- Approximate of Bayesian computation

- Bayesian Inference concepts

- Bayesian regression methods for linear regressions, splines,

- Time series #forecasting

- Bayesian additive regression trees

- Approximate of Bayesian computation

The book's authors are the contributors of PyMC3, ArviZ, Bambi, #TensorFlow Probability, and other #Python libraries:

PyMC3 - docs.pymc.io/en/v3/

Tensorflow Probability - tensorflow.org/probability

ArviZ - arviz-devs.github.io/arviz/

PyMC3 - docs.pymc.io/en/v3/

Tensorflow Probability - tensorflow.org/probability

ArviZ - arviz-devs.github.io/arviz/

This graph is now dynamically created based upon the latest @CDCofBC dashboard. #vaccineswork, even in the last month of this awful pandemic.

#stats #covidbc #bcpoli #epitwitter

/1

#stats #covidbc #bcpoli #epitwitter

/1

Raw data from @CDCofBC

@ATMNE_math panel discussions happening now! Being recorded for those who can't attend live.

Thanks @atomic_math!

Looking forward to panel on "Math 4 All" with @carloliwitter @mslailanur & Michelle McKnight

#MTBoS #iTeachMath

Thanks @atomic_math!

Looking forward to panel on "Math 4 All" with @carloliwitter @mslailanur & Michelle McKnight

#MTBoS #iTeachMath

Michelle: Math 4 All means all Ss see themselves as math do-ers & thinkers & communicators. No obstacles are being set up by us, so all Ss see themselves as "math people"

@mslailanur : Meet all Ss where they are

@mslailanur : Meet all Ss where they are

@mslailanur @carloliwitter Everyone should have the access to all the math, so everyone can have the opportunities & options.

Reminded of Bob Moses, radical equations.

Reminded of Bob Moses, radical equations.

hello #psychology #stats twitter!

a while ago i promised some graphs on why #removing #outliers using a simple cut-off (eg, >2SDs) is a #bad idea

so that I can sleep at night again, here they are

tldr: DON'T (blindly) USE FIXED OUTLIER CUT-OFFS LIKE >2SD. EVER.

1/15

a while ago i promised some graphs on why #removing #outliers using a simple cut-off (eg, >2SDs) is a #bad idea

so that I can sleep at night again, here they are

tldr: DON'T (blindly) USE FIXED OUTLIER CUT-OFFS LIKE >2SD. EVER.

1/15

some twitter background:

2/15

2/15

for some reason, it's very common in #psychology to remove 'outliers' from data

most common way: exclude data more than two standard deviations from mean

we spend time & money collecting data, then throw 5% away

🤷

I don't know why, or where it's taught, but there it is

3/15

most common way: exclude data more than two standard deviations from mean

we spend time & money collecting data, then throw 5% away

🤷

I don't know why, or where it's taught, but there it is

3/15

#ichimoku Pour faire suite à , le lien entre ce modèle 2A-A et pourquoi #Hosoda aurait construit #kinkohyo et #kumo de façon similaire, avec l'explication de la projection en 26 du Kumo.

(en attendant les vidéos d'@kieffer_herve 😉)

(en attendant les vidéos d'@kieffer_herve 😉)

1/ A thread on @pendle_fi, one of the most understimated projects that recently launched on mainnet. Pendle is a protocol that enables the trading and hedging of yield and currently supports two yield-generating tokens: aUSDC and cDAI, both products expire on December 29th, 2022.

2/ A deposit of aUSDC is separated into OT-aUSDC (OT represents the ownership of the underlying token deposited) and YT-aUSDC (representing the ownership of the future yield generated).

3/ @pendle_fi created a USDC liquidity pool for YT-aUSDC and YT-cDAI to price their markets, this is achieved providing incentives,

The latest figures about the 10000s of #britsinFrance #latvia #luxembourg #malta who haven't applied for residence makes alarming reading. With a #harddeadline of #30June, my latest piece for @ukandeu examines the #stats 1/

ukandeu.ac.uk/british-citize…

ukandeu.ac.uk/british-citize…

It addresses who might fall between the gaps - building in my experience in working with British citizens living in France over the course of the #brexitnegotiations 2/

research.gold.ac.uk/id/eprint/2977…

research.gold.ac.uk/id/eprint/2977…

And calls for these countries to extend their deadlines for applications and develop communication strategies to target hard-to-reach populations. And I'm not alone @BritishInEurope have released a statement to the same effect 3/⬇️⬇️⬇️britishineurope.org/articles/75313…