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Merge pull request #14 from PythonBiellaGroup/develop
add blog, brand identity and meetup
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exclude_from_blog: true | ||
--- | ||
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# Blog | ||
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{{ blog_content }} |
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title: New brand identity | ||
description: Introduction to the new community brand identity | ||
comments: true | ||
timetoread: true | ||
tags: | ||
- brand identity | ||
- design | ||
--- | ||
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# Our new brand identity | ||
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![Logo](../../static/images/blog/new_brand_identity.jpeg) | ||
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It's hard not to notice the radical change we've made to our image and communication in recent weeks. | ||
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In collaboration with [Gradient](https://www.hypergradient.it/), we've worked hard to develop a new digital identity and fresh iconography. | ||
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Renewing our identity has been a challenge, especially for a dynamic community like ours, but it was a necessary step to improve the quality of our educational service and make it more inclusive. | ||
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In our new design, [Gradient](https://www.hypergradient.it/) drew inspiration from the [zen of Python](https://pythonitalia.github.io/python-abc/Pyllole/99_Zen.html), the beating heart of this language. | ||
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Here's what we've done: | ||
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* We've opted for a black and white color palette to promote simplicity and accessibility. | ||
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* We exclusively use the Helvetica font for all text, as it's an open-source font accessible to everyone. | ||
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* Our iconography has been simplified and made clear, direct, and without frills - just how we like to be and operate. | ||
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* At the same time, we've aimed to be bold and modern. | ||
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Saying goodbye to the little bear that has accompanied us for the past 3 years was difficult, but we felt it was time for a change! | ||
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We hope you appreciate our new look as much as we do. |
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title: Nuova brand identity | ||
description: Presentazione della nuova brand identity della community | ||
comments: true | ||
timetoread: true | ||
tags: | ||
- brand identity | ||
- design | ||
--- | ||
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# La nostra nuova brand identity | ||
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![Logo](../../static/images/blog/new_brand_identity.jpeg) | ||
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È difficile non notare il cambio radicale che abbiamo apportato nelle ultime settimane alla nostra immagine e alla nostra comunicazione. | ||
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In collaborazione con [Gradient](https://www.hypergradient.it/), abbiamo lavorato duramente per sviluppare una nuova identità digitale e una fresca iconografia. | ||
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Rinnovare la nostra identità è stato una sfida, specialmente per una community così dinamica come la nostra, ma era un passo necessario per migliorare la qualità del nostro servizio formativo e renderlo più inclusivo. | ||
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Nel nostro nuovo design, [Gradient](https://www.hypergradient.it/) si è ispirata allo [zen di Python](https://pythonitalia.github.io/python-abc/Pyllole/99_Zen.html), il cuore pulsante di questo linguaggio. | ||
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Ecco cosa abbiamo fatto: | ||
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* Abbiamo scelto di adottare una palette di colori in bianco e nero, per favorire la semplicità e l'accessibilità. | ||
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* Utilizziamo esclusivamente il carattere Helvetica per tutti i testi, poiché è un font open source e accessibile a tutti. | ||
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* La nostra iconografia è stata semplificata e resa chiara, diretta e senza fronzoli - proprio come ci piace essere e come ci piace operare. | ||
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* Allo stesso tempo, abbiamo cercato di essere audaci e moderni. | ||
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È stato difficile dire addio all'orsetto che ci ha accompagnato per questi ultimi 3 anni, ma sentivamo che era giunto il momento di cambiare! | ||
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Ci auguriamo che apprezziate il nostro nuovo look tanto quanto noi. |
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title: Brand identity | ||
disquis: PythonBiellaGroup | ||
hide: | ||
- toc | ||
- feedback | ||
--- | ||
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# Brand identity | ||
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![Logo](../../static/images/brand_identity/pbg_brand_identity.gif) | ||
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At the heart of our community, the redesign presents itself not only as a visual metamorphosis but as a true manifesto of principles, where form meets function in an aesthetic embrace that celebrates clarity, precision, and openness. The new logo, bold in its simplicity, stands as a beacon of recognition, exuding a sober confidence in black and white that recalls the purity of intent and commitment to accessibility. | ||
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This renewed digital identity, forged in alliance with [Gradient](https://www.hypergradient.it/), draws deep inspiration from the [zen of Python](https://pythonitalia.github.io/python-abc/Pyllole/99_Zen.html), reflecting the very essence of the language in its minimalist elegance. The deliberate choice of a color palette restricted to black and white only, along with the exclusive adoption of the Helvetica font, is not just a tribute to functionality but an invitation to communion in the sign of accessibility and inclusion. The iconography, purified of any superfluity, speaks a language that is direct and essential, aiming to transcend visual simplicity to touch the true essence of communication. | ||
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The transition from the beloved bear symbol of our previous phase to this new expression of our being marks not only an aesthetic change but the transition to a new era of maturity and boldness. This evolution does not represent a break with the past but rather growth, an enrichment that, while respecting our roots, looks with new and courageous eyes towards the horizon of possibility. | ||
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We invite every member and observer to immerse themselves in this new dimension of PythonBiellaGroup, to be guided by the clean lines and defined contrasts of our new visual world, where every element is a bridge to knowledge, openness, and sharing. It is an open invitation to participate, to explore, and, above all, to grow with us in this adventure that, more than ever, celebrates the intrinsic beauty in simplicity, elegance, and community. |
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title: Brand identity | ||
disquis: PythonBiellaGroup | ||
hide: | ||
- toc | ||
- feedback | ||
--- | ||
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# Brand identity | ||
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![Logo](../../static/images/brand_identity/pbg_brand_identity.gif) | ||
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Nel cuore della nostra community, il rinnovamento del design si presenta non solo come una metamorfosi visiva ma come un vero e proprio manifesto di principi, dove la forma incontra la funzione in un abbraccio estetico che celebra la chiarezza, la precisione e l'apertura. Il nuovo logo, audace nella sua semplicità, si erge come un faro di riconoscibilità, trasudando una confidenza sobria nel bianco e nero che rievoca la purezza dell'intento e l'impegno verso l'accessibilità. | ||
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Questa rinnovata identità digitale, forgiata nell'alleanza con [Gradient](https://www.hypergradient.it/), s'ispira profondamente allo [zen di Python](https://pythonitalia.github.io/python-abc/Pyllole/99_Zen.html), riflettendo l'essenza stessa del linguaggio nella sua eleganza minimalista. La scelta rigorosa di una palette cromatica ristretta ai soli bianco e nero, oltre all'adozione esclusiva del font Helvetica, non è solo un omaggio alla funzionalità ma un invito alla comunione nel segno dell'accessibilità e dell'inclusione. L'iconografia, depurata da ogni superfluità, parla un linguaggio diretto e essenziale, mirando a trascendere la semplicità visiva per toccare la vera essenza della comunicazione. | ||
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La transizione dal caro orsetto simbolo della nostra precedente fase a questa nuova espressione del nostro essere non segna solo un cambiamento estetico ma il passaggio ad una nuova era di maturità e audacia. Questa evoluzione non rappresenta una rottura con il passato ma piuttosto una crescita, un arricchimento che, pur nel rispetto delle nostre radici, guarda con occhi nuovi e coraggiosi verso l'orizzonte del possibile. | ||
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Invitiamo ogni membro e osservatore a immergersi in questa nuova dimensione del PythonBiellaGroup, a lasciarsi guidare dalle linee pulite e dai contrasti definiti di questo nostro nuovo mondo visivo, dove ogni elemento è un ponte verso la conoscenza, l'apertura e la condivisione. È un invito aperto a partecipare, a esplorare e, soprattutto, a crescere insieme a noi in questa avventura che, più che mai, celebra la bellezza intrinseca nella semplicità, nell'eleganza e nella comunità. |
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--- | ||
title: Discovering large language model | ||
disquis: PythonBiellaGroup | ||
tags: | ||
- LLM | ||
--- | ||
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## Intro | ||
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In this session, we delved into Generative AI with a professional from [Data Masters](https://datamasters.it/), Giuseppe Mastrandrea, who guided us through the theory and practice of discovering Large Language Models (LLM). | ||
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Topics covered include: | ||
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* Introduction to Generative AI and LLM | ||
* Focus on latent spaces, embedding layers, and their training | ||
* Overview and initial experiments with "custom" agents, created by us | ||
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## Material | ||
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| | Link | | ||
|----------|----------| | ||
| Slides | [![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/blob/master/GenerativeAI/GenerativeAI_slides_01.pdf) | | ||
| Notebook | [![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1xIwMqN7JmBsheAEDKQ3CJWxPmzAfrC-Y?usp=sharing) | | ||
| LangChain | https://python.langchain.com/docs/get_started/introduction | | ||
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## Meetup video | ||
<iframe width="560" height="315" src="https://www.youtube.com/embed/E9U2p6mJuiY?si=Ex8QNycDGY8fO7gy" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe> |
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title: Alla scoperta dei Large Language Model | ||
disquis: PythonBiellaGroup | ||
tags: | ||
- LLM | ||
--- | ||
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## Intro | ||
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In questo incontro abbiamo parlato di Generative AI con un professionista di [Data Masters](https://datamasters.it/), Giuseppe Mastrandrea, che ci ha guidato tra teoria e pratica alla scoperta dei LLM. | ||
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I temi trattati sono: | ||
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* Introduzione alle generative AI e agli LLM | ||
* Focus su spazi latenti, layer di embedding e loro addestramento | ||
* Cenni e primi esperimenti con agenti "custom", ovvero creati da noi | ||
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## Materiale | ||
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| | Link | | ||
|----------|----------| | ||
| Slides | [![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/blob/master/GenerativeAI/GenerativeAI_slides_01.pdf) | | ||
| Notebook | [![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1xIwMqN7JmBsheAEDKQ3CJWxPmzAfrC-Y?usp=sharing) | | ||
| LangChain | https://python.langchain.com/docs/get_started/introduction | | ||
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## Video del meetup | ||
<iframe width="560" height="315" src="https://www.youtube.com/embed/E9U2p6mJuiY?si=Ex8QNycDGY8fO7gy" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe> |
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title: Building an intelligent agent with LangChain, Gradio, and OpenAI | ||
disquis: PythonBiellaGroup | ||
tags: | ||
- LLM | ||
--- | ||
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## Intro | ||
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In this second meeting dedicated to Generative AI, Vincenzo Maritati, a professional from [Data Masters](https://datamasters.it/), guided us through theory and practice in building our own intelligent agent using LangChain, Gradio, and OpenAI. | ||
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The topics covered during the session were: | ||
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* LangChain framework | ||
* Sequential Memory | ||
* Prompt Template | ||
* Analysis of the demo code | ||
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## Material | ||
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| | Link | | ||
|----------|----------| | ||
| Slides | [![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/blob/master/GenerativeAI/GenerativeAI_slides_02.pdf) | | ||
| Code | [![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/tree/master/GenerativeAI/Serata%2002) | | ||
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## Meetup video | ||
<iframe width="560" height="315" src="https://www.youtube.com/embed/m93keKjJe-c?si=1RbOCYN6iZhMwJAl" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe> |
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title: Come costruire un agente intelligente con LangChain, gradio e OpenAI | ||
disquis: PythonBiellaGroup | ||
tags: | ||
- LLM | ||
--- | ||
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## Intro | ||
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In questo secondo incontro dedicato alla Generative AI, Vincenzo Maritati, professionista di [Data Masters](https://datamasters.it/), ci ha guidato tra teoria e pratica attraverso la costruzione di un proprio agente intelligente sfruttando LangChain, gradio e OpenAi. | ||
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I temi trattati durante la serata sono stati: | ||
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* LangChain framework | ||
* Memoria Sequenziale | ||
* Prompt Template | ||
* Analisi del codice della demo | ||
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## Materiale | ||
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| | Link | | ||
|----------|----------| | ||
| Slides | [![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/blob/master/GenerativeAI/GenerativeAI_slides_02.pdf) | | ||
| Code | [![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/tree/master/GenerativeAI/Serata%2002) | | ||
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## Video del meetup | ||
<iframe width="560" height="315" src="https://www.youtube.com/embed/m93keKjJe-c?si=1RbOCYN6iZhMwJAl" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe> |
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title: Generative AI | ||
disquis: PythonBiellaGroup | ||
--- | ||
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## Intro | ||
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Here is our two-part series dedicated to exploring Generative AI and Large Language Models (LLM). This series will take you through the fundamental concepts and practical applications of these cutting-edge technologies in the field of artificial intelligence. | ||
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The series is curated by [Data Masters](https://datamasters.it/). | ||
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## Structure of the series | ||
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1. Introduction to the world of Generative AI and LLM | ||
2. Building an intelligent agent with LangChain, Gradio, and OpenAI | ||
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## Material | ||
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[![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/tree/master/GenerativeAI) |
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title: Generative AI | ||
disquis: PythonBiellaGroup | ||
--- | ||
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## Introduzione | ||
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Ecco il nostro percorso di due incontri dedicati all'esplorazione delle Generative AI e dei Large Language Models (LLM). Questo percorso vi condurrà attraverso i concetti fondamentali e le applicazioni pratiche di queste tecnologie all'avanguardia nell'ambito dell'intelligenza artificiale. | ||
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Il percorso é a cura di [Data Masters](https://datamasters.it/). | ||
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## Struttura del percorso | ||
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1. Introduzione al mondo delle generative AI e ai LLM | ||
2. Come costruire un agente intelligente con LangChain, gradio e OpenAI | ||
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## Materiale | ||
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[![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/tree/master/GenerativeAI) |
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title: Introduction to micropython | ||
disquis: PythonBiellaGroup | ||
--- | ||
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## Intro | ||
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MicroPython is a compact and optimized version of Python, designed to run on microcontrollers and embedded devices. It offers a complete and standard-compliant Python implementation on devices with limited resources, such as ARM Cortex-M microcontrollers. | ||
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MicroPython has become popular among makers because it allows them to write Python code to control and interact with their electronic devices in a simpler and more intuitive way compared to other more complex programming languages. | ||
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This series is curated by [Juna Salviati](https://www.linkedin.com/in/junasalviati/). | ||
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## Structure of the series | ||
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1. Introduction to the Maker World | ||
2. IoT, Cloud, and Examples using MicroPython | ||
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## Material | ||
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[![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/tree/master/MicroPython) | ||
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title: Introduzione a micropython | ||
disquis: PythonBiellaGroup | ||
--- | ||
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## Introduzione | ||
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MicroPython è una versione compatta e ottimizzata di Python, progettata per funzionare su microcontroller e dispositivi embedded. Offre un'implementazione Python completa e compatibile con lo standard su dispositivi con risorse limitate, come microcontrollori ARM Cortex-M. | ||
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MicroPython è diventato popolare tra i maker perché consente loro di scrivere codice Python per controllare e interagire con i loro dispositivi elettronici in modo più semplice e intuitivo rispetto ad altri linguaggi di programmazione più complessi. | ||
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La serie é a cura di [Juna Salviati](https://www.linkedin.com/in/junasalviati/). | ||
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## Struttura del percorso | ||
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1. Introduzione al mondo dei makers | ||
2. Iot, cloud ed esempi utilizzando micropython | ||
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## Materiale | ||
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[![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/tree/master/MicroPython) | ||
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title: Introduction to the makers world | ||
disquis: PythonBiellaGroup | ||
tags: | ||
- micropython | ||
--- | ||
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## Intro | ||
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MicroPython is a software implementation of the Python 3 programming language, written in C, optimized for running on microcontrollers. | ||
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It's an excellent tool for programming electronic boards, microcontrollers, and realizing projects for makers! | ||
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With [Juna Salviati](https://www.linkedin.com/in/junasalviati/), we delved into the world of electronics discussing: | ||
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* IoT, Microcontrollers, and Boards | ||
* Introduction to Electronics | ||
* Building a Thermometer | ||
* From Volts to Temperature | ||
* A use case: crop growth prediction | ||
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## Material | ||
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[![Github](https://img.shields.io/badge/GitHub-181717.svg?style=for-the-badge&logo=GitHub&logoColor=white)](https://github.com/PythonBiellaGroup/MaterialeSerate/blob/master/MicroPython/MicroPython%2001%20-%20Introduzione%20al%20mondo%20dei%20makers.pdf) | ||
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## Meetup video | ||
<iframe width="560" height="315" src="https://www.youtube.com/embed/vk00Vf_Gxc4?si=13S_3aROi2Jk-DRL" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe> |
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