Hi 👋, I am Osvaldo Martini

A passionate FullStack Developer

• 🔭 I am currently working as a Freelancer Open to opportunities

• 🌱 I'm currently delving into React Js | React Native

• 💬 Ask me about my Skills **React Js, React Native, JavaScript, Python **

• 📫 How to contact me: osvaldo.martini@gmail.com

• ⚡ Curiosities I'm funny and always in a good mood

• ⚡ Currently, I am working on a migration from Delphi Pascal (More than 60K lines of code done in 2004) for Java, Python, React, Kafka Stream, etc.

• If you want to participate, visit the repository: Algol

• YouTube: Random Number Map of Prediction: Past -> Present -> Future

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Some applied theorems:

$${P ( A | B ) = \frac {\left(\Sigma_{i=1}^{n}{P ( B | A ) }.{P ( A) }\right)^{∞}}{\Sigma_{i=1}^{n}v_{∞}{P ( B) }}}\quad \leq \quad ∞$$

$$\left( \sum_{k=1}^n a_k b_k \right)^2 \leq \left( \sum_{k=1}^n a_k^2 \right) \left( \sum_{k=1}^n b_k^2 \right)$$

$${\frac {\left(\Sigma_{i=1}^{n}u_{i}\right)^{2}}{\Sigma_{i=1}^{n}v_{i}}}\quad \leq \quad \sum_{i=1}^{n}{\frac {u_{i}^{2}}{v_{i}}}$$

$${\text{ or equivalently}}$$

$${\frac {\left(u_{1}+u_{2}+\cdots +u_{n}\right)^{2}}{v_{1}+v_{2}+\cdots +v_{n}}}\leq {\frac {u_{1}^{2}}{v_{1}}}+{\frac {u_{2}^{2}}{v_{2}}}+\cdots +{\frac {u_{n}^{2}}{v_{n}}}$$

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