Gabriel Castro

'In God we trust. All others must bring data.'
Dr. W. Edwards Deming

[Gabriel Castro @casmangabo]

@Suryanshti777 ROADMAP

[Suryansh Tiwari @Suryanshti777]

Most people want to become AI Engineers

Very few know what to learn next

That's why I'm giving away one of the best Agentic AI Engineer Roadmaps for FREE to the first 4500 people only

Inside you'll learn

✅ Python Fundamentals
✅ LLM Fundamentals
✅ LangChain LangGraph CrewAI AutoGen
✅ LCEL Runnables & Workflows
✅ Memory Systems
✅ Tool Integrations
✅ RAG Systems
✅ Multi Agent Systems
✅ Real World AI Projects
✅ Interview Questions & Answers

72 Hours Only

How to get

Follow me (so I can DM you)
Like + RT
Comment "ROADMAP"

Once the limit is reached I'll stop sending it.

[Gabriel Castro @casmangabo]

@BharukaShraddha AI

[Shraddha Bharuka @BharukaShraddha]

🎯 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 + 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 + 𝗔𝗜 — 𝗔𝗹𝗹 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁𝘀!

A complete bundle of cheat sheets from Stanford and MIT, covering everything from ML fundamentals to advanced AI concepts. 🚀

💡 Perfect for students, developers & AI enthusiasts who want quick, clear references while studying or building projects.

FREE Download for the first 500 people!📘

1️⃣ Like & Repost
2️⃣ Comment “AI”
3️⃣ Follow (so I can DM you)

Let’s make learning AI easier, one cheat sheet at a time. 🤖

#MachineLearning #DeepLearning #AI #Giveaway #Stanford #MIT #CheatSheets #AIEducation

[Gabriel Castro @casmangabo]

@juanjose2216211 @JoseCuelloB Hasta los chinos que hablan un idioma ancestral y milenario aprenden inglés

[Gabriel Castro @casmangabo]

@ThePhDPlace Just to train AI with these

[MentalidadFeroz @MentalidadFeroz]

Este tipo expuso la psicología que hay detrás de por qué compras cosas. Su nombre es Robert Cialdini.

Apple, Amazon y Nike utilizan sus 6 principios para dominar sus mercados.

Aquí están, y cómo puedes utilizarlos para influir en los demás:

[Juan Matías Sepulcre @JMSepulcre]

La Universidad de Luxemburgo dispone del recurso 'Visual Mathematical Dictionary', una nueva web destinada a facilitar el aprendizaje de términos matemáticos (también en castellano):
https://t.co/8kY2UjC8S1

[Gabriel Castro @casmangabo]

@HelmerDvila1 @EnsedeCiencia Y a pezuña de llama

[Gabriel Castro @casmangabo]

@NaranjoNoe @EnsedeCiencia El imperio azteca y el virreinato de la nueva españa no fueron lo mismo

[Mushtaq Bilal, PhD @MushtaqBilalPhD]

Repost this to win a FREE annual subscription to Research Kick.

If this gets 1,000 reposts, we'll give 3 random people who repost free subscriptions.

Research Kick helps you find research gaps and craft novel research questions in minutes.

🔗https://t.co/0w7HBmMvWk

[Gabriel Castro @casmangabo]

@OACerebro Por lo cual la oferta debería ser más apoyada (casi subsidiada) en los países en vías de desarrollo

[Rosana Ferrero 📈📊🙌 @RosanaFerrero]

📚Cómo ser un científico moderno (ahora en español)
La academia está cambiando. Ya no es suficiente con publicar o perecer. Necesitas estar al tanto de los desarrollos tecnológicos actuales que afectan a las carreras científicas modernas. @jtleek #book
https://t.co/lk3csqENjO

[Gabriel Castro @casmangabo]

@RosanaFerrero Y sin embargo R cuadrado es usado como indicador casi para todo lo anterior 😐

[Gabriel Castro @casmangabo]

@MincienciasCo @YeseniaOlayaR @MincomercioCo @CancilleriaCol @AlvaroLeyva @UNESCO_es Se necesita una revolución educativa y cultural, si la ciencia no hace parte de la cultura nacional, los avances serán poco o nada significativos

[elvis @omarsar0]

Accelerating the Science of Language Models

This is huge!

@allen_ai just released its first Open Language Model (OLMo), a 7B parameter model.

It includes open training code, open data, full model weights, evaluation code, and fine-tuning code.

It shows strong performance on many generative tasks.

There is also a smaller version of it, OLMo 1B.

I will be writing a complete prompting guide for this. Stay tuned!

This is brilliant work and will ignite even more research opportunities for the AI community.

[Matt Dancho (Business Science) @mdancho84]

XGBoost is now the go-to number 1 must-have algorithm in my data science toolkit. But for years, I had no clue what I was doing. In 3 minutes, I’ll share 3 months of research (business case included). Let’s go:

1. XGBoost, which stands for Extreme Gradient Boosting, is an advanced implementation of the gradient boosting machine (GBM) algorithm. It was developed to optimize both computational speed and model performance.

2. Gradient Boosting Machine (GBM): GBMs are an ensemble approach that combines multiple weak learners (typically decision trees) to create a strong predictive model.

3. Difference between GBM and Random Forest: Random Forest also uses decision trees. However, the difference is how the trees are developed. GBM sequentially adds weak learners (shorter trees), where each one corrects its predecessor. RF constructs strong learners (large trees) in parallel using Bootstrap Aggregation (Bagging).

4. Performance: XGBoost is an ultra-fast implementation of GBM that includes high-efficiency, scalability, ability to handle sparse data, parallel learning, and regularization to reduce over-fitting. XGBoost tends to be more efficient than Random Forest and traditional GBM, and often provides better performance. This is why I like it so much.

5. Business Use Cases: I use XGBoost in many business cases. Let’s start with the one that made the most impact, a $12,000,000 sales increase. Lead scoring. In 2 years of developing a Lead Scoring Model that made my company $12,000,000, I used a number of different algorithms. I started with the most basic- Logistic Regression for classification probability of a customer purchasing. And over time, improved it with better algorithms, better and more complex features. The final iteration had XGBoost as a key model in the algorithm.

6. Business Use Case (Time Series): I later discovered that I could use XGBoost on time series for forecasting sales demand at the product level. This was a major improvement over less-scalable techniques (ARIMA, ETS) that had to be run iteratively on every product. We had 12,000+ products. XGBoost cut training times from 3 days to about 4 minutes. One thing to watch out for is that because it’s tree-based, XGBoost cannot predict beyond the maximum or below the minimum in a dataset. So differencing may be required.

===

There’s a lot more to learning Data Science for Business than just XGBoost. I’d like to help.

I put together a free on-demand workshop that covers the 10 skills that helped me make the transition to Data Scientist: https://t.co/LR39RJ5XKB

And if you'd like to speed it up, I have a live workshop where I'll share how to use ChatGPT for Data Science: https://t.co/EaMpKrJiqX

If you like this post, please reshare ♻️ it so others can get value.

[Tom Mitchell @tommitchelldata]

Learn Data Analysis For Free in 2024:

1. Excel
https://t.co/q0kqfvNA5Y

2. SQL
https://t.co/kFdmcldVZ5

3. PowerBI
Reports in PowerBI (Datacamp)
https://t.co/oK3MRQOdio

4. Tableau
https://t.co/SzvZOzdMUD

5. Python
https://t.co/pxILdmBKfd

6. R
https://t.co/GAHe0hKvij

Make 2024 your year.

[Python Space @python_spaces]

Microsoft is offering Data Science for Beginners for FREE

- 10 Weeks
- 20 Lessons

100% Free

Find course link 🧵👇

[Kirk Borne @KirkDBorne]

Understanding #DeepLearning (download 541-page PDF eBook): https://t.co/Z3ZjaEmMcO by @SimonPrinceAI
——————
#BigData #DataScience #AI #ML #MachineLearning #NeuralNetworks #ReinforcementLearning #NLProc #ComputerVision #Algorithms #DataScientists #mathematics