FeiderED

La riqueza de la humanidad son sus ideas 💚
🌎 World is Data
🎬 Audiovisuales
💼 Emprendimiento
🦄 Unicornio
#NeverstopGrowing

[Felipe | Robot.com @felipekiwi90]

Platzi Conf: https://t.co/q0R1tEFk5G

[FeiderED @FeiderED]

Today I have passed the course "Estrategias para Aprender Inglés en Línea" at @Platzi!, the team at @PlatziAcademy are amazing, they have made me change my opinion about learning English and other languages
https://t.co/J1BBj9bR8v

[FeiderED @FeiderED]

@platzi Estoy comenzando con Introducción a excel para principiantes

[FeiderED @FeiderED]

Today I bought a subscription on @platzi to learn more about programming and improve my English with @PlatziAcademy. I also want to start a YouTube channel and create a brand with the name Feider. All of this documented here in @X

[OpenAI @OpenAI]

🤝😍

[Brais Moure @MoureDev]

Aquí está la 2ᵃ edición de mi libro: "Git & GitHub desde cero"

¿Lo celebramos REGALANDO 10?
✅ Sígueme
❤️ Dale like
🔁 Haz RT

El viernes hago el sorteo.
Mil gracias por todo el apoyo durante este año!

[FeiderED @FeiderED]

@MrBeast Gogogo

[MrBeast @MrBeast]

I’m gonna give 10 random people that repost this and follow me $25,000 for fun (the $250,000 my X video made)

I’ll pick the winners in 72 hours

[Lior Alexander @LiorOnAI]

Impressive. Microsoft released a new method to speed up LLM inference, boost performance, while making them 20x smaller.

Massive cost reduction with almost no performance loss.

You can implement it in 2 minutes using their library:
!pip install llmlingua

LLMLingua uses a compact, well-trained language model (e.g., GPT2-small, LLaMA-7B) to identify and remove non-essential tokens in prompts.

[Dr Milan Milanović @milan_milanovic]

𝗧𝗵𝗲 𝗚𝗿𝗲𝗮𝘁𝗲𝘀𝘁 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗕𝗼𝗼𝗸𝘀 𝗼𝗳 𝗔𝗹𝗹 𝗧𝗶𝗺𝗲

A question is often asked: should I read books to become a better developer? Usually, the answer is yes, and the reason for that is that the person who wrote the book wrote it when (𝘀)𝗵𝗲 𝘄𝗮𝘀 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗶𝗻𝘃𝗶𝘁𝗲𝗱 𝘁𝗼 𝘄𝗿𝗶𝘁𝗲 𝗶𝘁 with the most extensive knowledge base then. The only better option would be to work with that person, which is often impossible.

Yet, many people need to read more, which means if you read books, you will be 𝗮𝗵𝗲𝗮𝗱 𝗼𝗳 𝗼𝘁𝗵𝗲𝗿𝘀 by a few marks. During the years, I developed a routine of reading a lot of books, so taking into account my own experience and the experience of many peers I spoke with, I compiled a list of the most excellent books that every software developer should read at one point in a career (tech agnostic):

𝟭. 𝗖𝗹𝗲𝗮𝗻 𝗖𝗼𝗱𝗲 - One of the most excellent software development books ever written by Uncle Bob Martin in 2008. It is written to teach software engineers the principles of writing clean programming code. There are a lot of examples inside, showing how to refactor code to be more readable and maintainable using SOLID principles.

𝟮. 𝗧𝗵𝗲 𝗣𝗿𝗮𝗴𝗺𝗮𝘁𝗶𝗰 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗲𝗿 - This book is filled with technical and professional practical advice for developers to become better developers. It examines what it means to be a modern developer by going through topics that range from personal responsibility and career development to architectural techniques.

𝟯. 𝗖𝗼𝗱𝗲 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 - Some people consider this book one of the best practical guides to programming, recommended to beginners. It deals with design, coding, debugging, and testing. In more than 900 pages, the authors describe how to write programs for people first and then for computers second and how to master the human qualities of top coders.

𝟰. 𝗛𝗲𝗮𝗱 𝗙𝗶𝗿𝘀𝘁 𝗗𝗲𝘀𝗶𝗴𝗻 𝗣𝗮𝘁���𝗲𝗿𝗻𝘀 - It describes main software design patterns in three categories to create more flexible, elegant, and reusable designs without rediscovering the design solutions. It is a must-read for an architect or developer of a complex system.

𝟱. 𝗥𝗲𝗳𝗮𝗰𝘁𝗼𝗿𝗶𝗻𝗴 - In this book, Martin Fowler writes about improving the design of an existing code. It represents refactoring as a process of changing a software system in a way that does not alter the code's external behavior but improves its internal structure. Using refactoring as a technique, it's possible to take a bad design and rework it into a good one.

𝟲. 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 - One of the most famous books on all kinds of algorithms in depth (also known as CLRS). It represents a comprehensive guide to all readers, from beginners to professionals. Each chapter is self-contained and can be used as a unit of study. Algorithms are described in English and pseudocode, so one can be familiar even with someone who didn't do much coding.

��. 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝗻𝗱 𝗜𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀 - This book is one of the best for learning programming fundamentals (SICP). The book explains the four best-known paradigms of programming languages: imperative, logic-based, object-oriented, and applicative programming.

𝟴. 𝗪𝗼𝗿𝗸𝗶𝗻𝗴 𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲𝗹𝘆 𝘄𝗶𝘁𝗵 𝗟𝗲𝗴𝗮𝗰𝘆 𝗖𝗼𝗱𝗲 - Michael Feathers offers different strategies for dealing with large and untested legacy code bases in this book. The book is essential, as almost every developer has to work with a legacy system at some point in their career, and it still represents one of the most challenging problems for many companies.

𝟵. 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗣𝗲𝗮𝗿𝗹𝘀 - The book represents one of the most influential books that help a person think as a programmer. Every concept in the book is covered with practical problems and various solutions. The book challenges the reader to understand the core concepts in memory, CPU, and algorithms, increasing difficulties rather than answering immediately.

𝟭𝟬. 𝗗𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗗𝗮𝘁𝗮-𝗜𝗻𝘁𝗲𝗻𝘀𝗶𝘃𝗲 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 - One of the best books on data-intensive applications. The book describes concepts such as databases and data models and a deep dive into distributed concepts, such as transactions, replication, consistency, etc.

#programming #learning

[Omar Sanseviero @osanseviero]

LLM Visualization: Amazing animated interactive tutorial to learn about GPT internals

https://t.co/SZhU26pZA8

[Kamran Ahmed @nilbuild]

✨ AWS Roadmap ✨

We just published a new interactive guide for learning AWS. We are also planning on running an experiment with a task based roadmap for this one, so stay tuned for that as well.

Check it out 👇

https://t.co/KG5UgzOj0H

[Dan Kornas @DanKornas]

👉 Machine Learning Projects And Tutorials

In this repository you will find tutorials and projects related to Machine Learning.

🔗 https://t.co/REc7VaPkOX

[Anders Liu-Lindberg @LiuLindberg]

Learn Financial Analysis 101 for free.

Save 1,000s of dollars.

Let's dig into the curriculum.

6 Modules and 28 Lessons 🧵.

[Python Coding @clcoding]

Free Web Scraping using Python https://t.co/AQrQ0eWCRG

[Brais Moure @MoureDev]

Python y JavaScript son 2 de los lenguajes más utilizados en la actualidad...

¿Y si te digo que puedes combinarlos?

¡Python Monkey permite utilizar JS desde Python y viceversa!

🐵 https://t.co/M7XTO3ErDm

[leonie @helloiamleonie]

I can't believe I won 1st place in the 2023 Kaggle AI Report competition in the category "Kaggle Competitions"! 🥳

Thank you to the @kaggle team and the judges for organizing this competition and judging all the great entries.

You can find my entry here: https://t.co/5zFBcm7nzm

[Save to Notion  @SaveToNotion]

Big things are on the horizon! 🌟