Discover and read the best of Twitter Threads about #Arima

Most recents (7)

@nixtlainc started last year as a side project

Today we reached 1 million downloads🎉

Our goal is to shake the time series industry and make state-of-the-art algorithms available for everyone 🔥

This is how we got there

🧵1/11

#reinventforecasting
@nixtlainc's ecosystem consists (now) of 5 #python libraries

Focus: speed, scalability, and accuracy 🚀

Some features:
* @scikit_learn syntax
* Native support for #spark, @raydistributed, and @dask_dev
* Models! Eg #arima, #LightGBM, #NeuralNetworks, #transformers 🤖

2/11 Image
We are really proud of the open-source adoption

Repos from Amazon, Mozilla, and DataBricks use us as dependencies 🏄‍♂️

We have contributions from people working at H20, Microsoft, Google, Facebook, SalesForce, Oracle, Shopify, AT&T, Blueyonder, Stanford, MIT and UCL 🙏

3/11
Read 12 tweets
Let's continue with the #TimeSeries forecasting 😀

We want to use an #ARIMA to forecast the #BTC price. But... how can we select its parameters?

#machinelearning #python #datascience Image
Let's first start with "p" and "q".

For this, we need to check how correlated the time series is with lagged versions of itself.

The original time series will be denoted as 0. A 1-timestep lagged version will be referred to as 1. And so on...
The correlation of the original time series with the lag 0 (no lagged), will always be equal to 1, since they are the same time series.

The questions are...
• What is the correlation of the original time series with lag 1?
• What about lag 2?
• And 3, 4, 5...?
Read 10 tweets
I have started the #TimeSeries project about predicting Bitcoin #BTC price.

First I am going to try a traditional method: #ARIMA. Will it work? 🤔

If you don't know what it is 🧵👇

#datascience #artificialintelligence #machinelearning
It is composed of 3 elements:
1️⃣ AR: Auto-Regressive
2️⃣ I: Integrated
3️⃣ MA: Moving Average

Let's introduce them... 👇
1️⃣ [ AR ]-IMA

🔎It takes into account "p" previous values, in my case previous #BTC prices.

🔮To make the prediction it relies on the previous prices.
Read 7 tweets
Peut-on mieux anticiper la dynamique hospitalière de #COVID19 à l’aide des données numériques de mobilité ?

Des travaux de Christian Selinger (@ird_fr) avec @samuel_alizon (@CNRS) et @choisy_marc (@OUCRU_Vietnam) sont publiés en août sur ce sujet.

ijidonline.com/article/S1201-…

1/N
Grâce à un partenariat avec l’opération @DataForGood_FR de @FacebookFR et l’@umontpellier, l'équipe a pu valider un modèle qui vise à expliquer les variations des nombres quotidiens d’admission et de décès à l'hôpital pour #COVID19.

dataforgood.fr

2/N
L’originalité de l’approche réside dans le modèle et les données utilisées.

@FacebookFR donne accès à des données de #colocalisation entre 2 personnes, plus appropriées pour une épidémie car reflètant un #contact (et non juste la position d'une personne).

3/N
Read 11 tweets
Le preprint de notre analyse des #Ct des tests #RTPCR de #SARSCoV2, en partenariat avec la Société Française de Microbiologie et plus de 20 laboratoires de virologie français est maintenant en ligne. **NON RELU PAR LES PAIRS**

medrxiv.org/content/10.110…
1/N
Nous y analysons des valeurs quantitatives de millions de tests #RTPCR effectués en France en 2020 : les Ct, ou cycles de doublement.

assets.publishing.service.gov.uk/government/upl… (doc très clair en anglais)

publichealthontario.ca/-/media/docume… (doc en français)

**NON RELU PAR LES PAIRS**
2/N
Il y a eu un débat sur ces Ct et l'opportunité de les communiquer aux patients.

Primo, cela dépend de l'échantillon. Secundo, pour les #coronavirus, il est risqué de voir dans le nombre de copies d'ARN une charge virale.
osf.io/5gra3/

**NON RELU PAR LES PAIRS**
3/N
Read 11 tweets
D1 of #50daysofudacity
I finished up to Lesson 2.19
My notes can be found here for quick refernce
docs.google.com/document/u/1/d…
D2 of #50daysofUdacity
I finished up to Lesson 2.25
Also completed lab assignment for a linear regression model to predict the price of taxi in new york city
My notes can be found here for quick reference

docs.google.com/document/u/1/d…
D3 of #50daysofudacity
I finished Lesson 2
Also completed lab assignment for linear regression model to predict the price of taxi in new york city
My notes can be found here for quick reference
docs.google.com/document/u/1/d…
Read 53 tweets
If people read US Defense Secretacy @EsperDoD speech, it is clear that USArmy is not between Turkish Army and PKK Terrorists,the later one (PKK) is called as ally by USA
@Newsweek @Independent @ehamedya @ragipsoylu @OmerOzkizilcik @malikejder_ @haskologlu
@EsperDoD @Newsweek @Independent @ragipsoylu @OmerOzkizilcik @malikejder_ @haskologlu After @EsperDoD speech, according to agreement between Turkish Army & US Army, (all US ground troops GPS coordinates have aldreay given), Turkish AirForce and other forces started to bomb some locations in west part of Ayn El Arab (PKK renamed it as Kobani)
@EsperDoD @Newsweek @Independent @ragipsoylu @OmerOzkizilcik @malikejder_ @haskologlu That is clear that Western Media are trying to spread "fake news" against US President @realDonaldTrump to be able to create an pressure in public. Already Turkey continues to operation according to the talk between Mr. Trump and President of Turkey, Mr. @RTErdogan.
Read 497 tweets

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