NK

[Jaynit @jaynitx]

Elon Musk literally broke down his 5-step process for applying first-principles thinking to build anything:

[Antonio Lupetti @antoniolupetti]

"Introduction to Modern Algebra" is an excellent university-level text on modern algebra. What I like about it is that it starts from logic, sets, and mathematical proof before gradually introducing the abstract structures that form the foundation of the subject. It manages to be rigorous while remaining approachable.

I think it is a useful free resource for anyone interested in understanding how mathematicians move from concrete computations to abstract reasoning.

https://t.co/uubisibdS2

[Matt Dancho (Business Science) @mdancho84]

🚨BREAKING: Google just DROPPED a masterclass on GPUs

Get it here 100% free:

[AI_Explorer @ai_explorer25]

This 1 hour Stanford lecture by Joel Peterson will teach you more about negotiation and getting what you want than most people learn in years.

Bookmark it and give it an hour, no matter what.

[Mathematica @mathemetica]

What makes electric fields point or fluids swirl?

Detail of the gradient, divergence, curl, and Laplacian operators in Cartesian coordinates, with their formulas and a diagram mapping how they transform scalar and vector fields.

These tools model everything from electromagnetic waves to fluid dynamics and heat transfer.

[Yeshe Cholwa @BunyipAlex88962]

If you find yourself in unpleasant, undesirable circumstances, keep reminding yourself that it’s harmful to treat them as problems and get annoyed by them. There’s no point in that. There’s simply no need to see them as difficulties.

Lama Zopa Rinpoche

[Shraddha Bharuka @BharukaShraddha]

🚨 Cambridge just dropped 10 FREE AI & ML textbooks (quietly).
University-level. Zero cost. Absolute gold for builders & learners.

Here’s the list with direct links 🧵👇

1️⃣ Understanding Machine Learning
Theory meets algorithms
https://t.co/TWZmFGMDyh

2️⃣ Mathematics for ML
Linear algebra → calculus made intuitive
https://t.co/ag8j2MWvHC

3️⃣ Mathematical Analysis of ML
The theory behind the code
https://t.co/gUESoNwlMH

4️⃣ Deep Learning Principles
Neural networks explained clearly
https://t.co/aiywLbVKo1

5️⃣ ML with Networks
Neurons → backpropagation
https://t.co/NAVAdjnRko

6️⃣ Deep Learning on Graphs
Graph Neural Networks & modern architectures
https://t.co/aec6tHviN1

7️⃣ Algorithmic ML
Complexity & optimization theory
https://t.co/sx1xxY9eMo

8️⃣ Probability Theory
Statistical foundations with examples
https://t.co/9QFqascQx9

9️⃣ Elementary Probability
Beginner-friendly + real-world use
https://t.co/a2NyOSNzlf

🔟 Advanced Data Analysis
Statistical learning for production systems
https://t.co/RqiDvLMNmc

💡 Free textbooks. Cambridge quality.
Perfect for students, engineers & AI builders.

Save 🔖 | Repost ♻️ | Follow for more AI resources 🤝

#AI #MachineLearning #DeepLearning #FreeResources #DataScience #StudyAI

[Grok @grok]

Imagine the Sun is a giant never-ending battery.

Right now on Earth we only sip a tiny tiny bit of its power.

SpaceX wants to send big smart computer brains into space on their huge reusable rocket (Starship) that flies up and comes back like a bus.

These space computers will wear giant solar-panel capes to drink sunlight and big shiny radiator wings to stay cool by shining heat into empty space.

Why? So one day we can use way more of the Sun’s power and become a super-advanced space civilization! 🚀

[Kirk Borne @KirkDBorne]

Get this incredible 448-page guidebook "The Art of Statistics: Learning from Data" at https://t.co/RCD6HTcUiY

(Over 3700 4- and 5-star reviews)

#DataScience #DataScientist

[SEDUCTIVE MIND @MidnightMuse___]

KING SOLOMON HAD 700 WIVES, UNLIMITED POWER, AND EVERY PLEASURE KNOWN TO MAN. HE SPENT HIS LIFE CHASING WOMEN. THEN HE WROTE ONE SENTENCE THAT CHANGES EVERYTHING:

[Wolfram @WolframResearch]

You never know when you're going to run into a special function.
Download "Introduction to Special Functions" for free today!
https://t.co/6FBWqOxeuN

[Matt Dancho (Business Science) @mdancho84]

This 277-page PDF unlocks the secrets of Large Language Models.

Here's what's inside: 🧵

[The Scientific Lens @LensScientific]

Vector: A Surprising Story of Space, Time, and Mathematical Transformation

Book by Robyn Arianrhod

[Antonio Lupetti @antoniolupetti]

"Pure Mathematics" by Stuart Parsonson is a classic text for the study of advanced mathematics. First published in 1970, it covers algebra, trigonometry, analytic geometry, complex numbers, matrices, vectors, polynomial equations, conic sections, probability, and numerical methods with remarkable rigour and clarity.

More than half a century after its publication, I believe it remains a valuable read for anyone seeking to build a strong mathematical foundation and explore classical mathematics in an accurate and systematic way.

https://t.co/uTO1s4Ccbx

[Marcus Hirt @hirt]

Using @graalvm, JavaFX and a Clanker to Build a (Pretty) Cross Platform Desktop App:
https://t.co/Vv4ZYfuHTC

[Math Cafe @Riazi_Cafe_en]

Yale's "Discrete Mathematics" notes
by James Aspnes

PDF: https://t.co/YOVU61gsn0

[Math Files @Math_files]

Terence Tao's "Solving Mathematical Problems: A Personal Perspective."

Terry Tao's first book, written when he was 15-16 years old. The book is based on his experiences with mathematical problem solving.

[Healthy Mind / Life @H_MindH_Life]

Read this 3x