Camila⭐️

La vida del rock.

[Camila⭐️ @camilacguzman]

Que la paz sea el único camino.

[Camila⭐️ @camilacguzman]

@juandaza1997 De 5 jajaja te amo

[Camila⭐️ @camilacguzman]

No soporto una tusa futbolera más. Me retiro

[Camila⭐️ @camilacguzman]

El mejor parche del mundo mundial Is Back.

[Camila⭐️ @camilacguzman]

La felicidad de ayer no tiene nombre. Ver el partido de Colombia con las personas que amo y que además comparten la pasión por el mejor deporte del mundo 🧡🍀
Juanca volvió y con él se fueron mis horas de sueño, pero la bienvenida ha estado completa ✨

[Camila⭐️ @camilacguzman]

La maravillosa lucidez de la ira.

[Camila⭐️ @camilacguzman]

@una_nube_ La mejor del mundo mundial 🧡

[Camila⭐️ @camilacguzman]

@LangeRriaMa Yo puedo ayudarla a cumplir el primer sueño 👀

[Camila⭐️ @camilacguzman]

@Arteymas_ @natxlxa falta la mejor de todas

[Matt Dancho (Business Science) @mdancho84]

Principal Component Analysis (PCA) is the gold standard in dimensionality reduction with uses in business. In 5 minutes, I'll teach you what took me 5 weeks. Let's go!

1. What is PCA?: PCA is a statistical technique used in data analysis, mainly for dimensionality reduction. It's beneficial when dealing with large datasets with many variables, and it helps simplify the data's complexity while retaining as much variability as possible.

2. How PCA Works: PCA has 5 steps; Standardization, Covariance Matrix Computation, Eigen Vector Calculation, Choosing Principal Components, and Transforming the data.

3. Standardization: The first step in PCA is to standardize the data. Since the scale of the data influences PCA, standardizing the data (giving it mean of 0 and variance of 1) ensures that the analysis is not biased towards variables with greater magnitude.

4. Covariance Matrix Computation: PCA looks at the variance and the covariance of the data. Variance is a measure of the variability of a single feature, and covariance is a measure of how much two features change together. The covariance matrix is a table where each element represents the covariance between two features.

5. Eigenvalue and Eigenvector Calculation: From the covariance matrix, eigenvalues and eigenvectors are calculated. Eigenvectors are the directions of the axes where there is the most variance (i.e., the principal components), and eigenvalues are coefficients attached to eigenvectors that give the amount of variance carried in each Principal Component.

6. Choosing Principal Components: The eigenvectors are sorted by their eigenvalues in descending order. This gives the components in order of significance. Here, you decide how many principal components to keep. This is often based on the cumulative explained variance ratio, which is the amount of variance explained by each of the selected components.

7. Transforming Data: Finally, the original data is projected onto the principal components (eigenvectors) to transform the data into a new space. This results in a new dataset where the variables are uncorrelated and where the first few variables retain most of the variability of the original data.

8. Evaluation: Each PCA component accounts for a certain amount of the total variance in a dataset. The cumulative proportion of variance explained is just the cumulative sum of each PCA's variance explained.

There you have it- my top 6 concepts on PCA. The next problem you'll face is how to apply data science to business.

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[Camila⭐️ @camilacguzman]

Volví después de un año a retweetearme y a decir que creo firmemente en el alargue.

[Camila⭐️ @camilacguzman]

Deberían suprimir los penales. Que aleatoriedad tan hijueputa

[Camila⭐️ @camilacguzman]

De una de las mejores noches de mi vida, en la cuna de tantos magos 🇦🇷🎸
Eterna vida al Rock y a sus grandiosos exponentes.

[Fito Paez @FitoPaezMusica]

Gracias a toda la muchachada en La Plata!. Que final de gira! Mañana es la última, última!
Cuanto amor y entrega! Cuanta buena vibra!. La música es un regalo de la vida!. Todo mi amor y gratitud a cada una de las personas que hoy participaron de esta hoguera emocional!

[Fito Paez @FitoPaezMusica]

Gracias a toda la muchachada en La Plata!. Que final de gira! Mañana es la última, última!
Cuanto amor y entrega! Cuanta buena vibra!. La música es un regalo de la vida!. Todo mi amor y gratitud a cada una de las personas que hoy participaron de esta hoguera emocional!

[Camila⭐️ @camilacguzman]

@FitoPaezMusica Qué noche la que nos diste, inolvidable!!! Haces magia con esa música que nos da vida a tantos. Larga vida al Rock 🌈🧡✨🤟🏽

[Camila⭐️ @camilacguzman]

Este capítulo de mi vida se llama: Andes Mágicos⛰️

[Camila⭐️ @camilacguzman]

Cumplir sueños se llama: Llegar al desierto de Atacama con rock chileno de fondo.

[Camila⭐️ @camilacguzman]

Pasar de tener que ir al hospital de los guayabos que me daban a poder ir a nadar al otro día que salgo de fiesta se llama calidad de vida. La prueba de que la medicina homeopática y las sales funcionan ✨

[Camila⭐️ @camilacguzman]

Mi gente, siempre mi gente.

[Camila⭐️ @camilacguzman]

@andresv48151623 Te amo

[Camila⭐️ @camilacguzman]

@_alejandrosaav @LangeRriaMa @andresv48151623 T amo