#mathforml 搜尋結果

📘 Grab the free “Mathematics for Machine Learning” book and strengthen your ML foundations in linear algebra, calculus, probability, and optimization. Download: mml-book.github.io/book/mml-book.… #MachineLearning #MathForML #AI #DataScience #MLBook

Next up → Essence of Calculus. Time to understand how optimization actually “learns.” Quietly building foundations strong enough to carry the weight of everything I want to create later. #MachineLearning #AI #MathForML #3Blue1Brown #LearningInPublic

Understanding symmetric matrices and positive definiteness is key to mastering #MachineLearning. They explain why algorithms like gradient descent actually converge! 🎥 Watch here → youtu.be/CgdJqxn0dlA #MathForML #AI #DeepLearning #LinearAlgebra

Dot product sounds scary — until you see it for what it really is: 👉 A way to measure alignment 👉 A key to cosine similarity 👉 The engine behind transformers Here’s what I learned today about this tiny but mighty math tool 🧠👇 #MLZoomcamp #mathforml #dotproduct

Phase 2: Mathematical Intuition 📐 Time: 2–6 hrs No PhD needed! Build intuition, not memorization. Watch🔗youtube.com/watch?v=BZYuCW… Then🔗youtube.com/watch?v=1VSZtN… Goal: Understand the "why" behind ML. Don’t stress if it’s fuzzy! #MathForML

Can someone confirm my explanation of 2x2 matrix multiplication? #MathForML

✨ What is the Dot Product & why it matters in ML Multiply matching vector elements ➕ sum them up: A · B = |A||B|cos(θ) 🔹 Measures similarity 🔹 Powers neural nets, attention, and cosine similarity Tiny math → big insights! #Day77 of #NeuralNetworkJourney #MathForML…

Just found @geogebra — one of the best tools I’ve seen for understanding math visually. Super helpful for grasping ML topics like vectors, functions, and calculus. 🔗 geogebra.org Definitely worth checking out! #MathForML #GeoGebra #LearnInPublic

🧠 Solving A·X = B in ML 🔹 Matrix Inverse: X = A⁻¹·B (only if A is invertible) 🔹 Gaussian Elimination: Systematically reduces equations → solution This math powers linear regression, optimization & neural nets! #Day75 of #NeuralNetworkJourney #MathForML #AI #LinearAlgebra…

Math for ml day 3 Today i've learned math induction, and now i'm going to learn trigonometry #mathforml

🚀 Milestone: Finished training in Statistics, Calculus & Algebra—the math powering ML! Excited to use these skills to build smarter models and explore real-world projects. Next: hands-on ML! #MachineLearning #AI #MathForML

Stop wondering why your model’s not improving, it's not stuck, it's just converging slowly. 📘 Understand the math behind the motion → landing.packtpub.com/mathematics-of… #LinearityOfConvergence #MathForML #100DaysOfMathematicsOfML

Today's ML math grind: • Got comfy with linear independence • Explored Matrices - Different types • Practiced coefficient labeling in systems of equations Slowly but surely building the foundation 💪📐 #MLjourney #MathForML

Wrapped up Eigenvalues & Eigenvectors today 🔥 Feels wild to finally understand how they power so many ML concepts. Almost at the end of my Linear Algebra journey — let’s go! 🚀 #MathForML #MachineLearning #LinearAlgebra #BuildInPublic #LearnInPublic #AI #MLCommunity

Why is RREF so crucial? It's the bedrock for solving linear systems efficiently, a skill directly applied in countless ML algorithms. Understanding it demystifies matrix operations and empowers your analytical journey. #MathForML #AI #DeepLearning

great. so I can finally conclude on why we need to master multivariate calculus, one of them is that u can help someone who dropped their phone on a deep sandpit. #mathforML #Coursera #Bangkit2021

Can someone confirm my explanation of 2x2 matrix multiplication? #MathForML

Math for ml day 3 Today i've learned math induction, and now i'm going to learn trigonometry #mathforml

Today's ML math grind: • Got comfy with linear independence • Explored Matrices - Different types • Practiced coefficient labeling in systems of equations Slowly but surely building the foundation 💪📐 #MLjourney #MathForML

Me: I’ll just “start” this ML Math course Also me: Finishes it in a day, earns 670 XP, unlocks badge Brain: Now loading eigenvectors... #MLMathr #MathForML #GrindSet 🧠💪

📏 What is Euclidean Distance? It’s the “straight-line” distance between two points in space: Think Pythagoras — but extended to n dimensions. #EuclideanDistance #MathForML #MachineLearning

Feeling a bit stupid for writing code to count lines of text, when I could have just looked at the side of the editor... 🤦‍♂️😂 __________ #javascript #Developer #mathforml

🚀 Milestone: Finished training in Statistics, Calculus & Algebra—the math powering ML! Excited to use these skills to build smarter models and explore real-world projects. Next: hands-on ML! #MachineLearning #AI #MathForML

اكتشف أهم قراءات مايو لمهندسي التعلم الآلي! من الرياضيات الأساسية إلى بروتوكولات الوكلاء، تجد كل ما تحتاجه لتعزيز معرفتك. اقرأ المزيد هنا! #MachineLearning #DataScience #MathForML #LLMs

Making a tree-diagram cheat sheet for probability counting problems. 🤗 First leaf: The multinomial Coefficient #mathforml

𝑓∘𝑔, you must have come across this in some Machine Learning course or a paper and wondered what it is! In this thread we will introduce you to some common math notations seen in ML. A thread 👇 #mathematics #MathforML #DeepLearning

Matematika itu indah. Di balik setiap model ML ada logika elegan dari matematika. Jangan menghindarinya, taklukkan ia! Ini adalah superpower rahasiamu. 🧠✖️ #MathForML #Algorithm #Logic

Overview of data distributions disq.us/t/3pg0vra . Probability distributions- always find them a challenging topic. Wish I had this before. #Stats #Probability #MathforML

Cracking the code of Machine Learning with Mathematics! 🧮💻 Dive into our latest tips on mastering the math essentials for ML. Linear algebra, statistics, and more - we're making it simple and fun! #MathForML #MachineLearningBasics #DataScience 📊🤖

Essential Math for Machine Learning: Kernel Density Estimation➡️medium.com/@weidagang/ess… #AIforBeginners #DataAnalysis #MathForML #artmac #artmacllc

SVD : write any matrix as summation of some rank one matrices. is this somewhat analogous to Taylor expansion of functions but surely not till infinite terms ? and so the SVD helps in many optimization problems aswell !! #mathematics #mathforml #MachineLearning #linearalgebra

Stop wondering why your model’s not improving, it's not stuck, it's just converging slowly. 📘 Understand the math behind the motion → landing.packtpub.com/mathematics-of… #LinearityOfConvergence #MathForML #100DaysOfMathematicsOfML

📘 Grab the free “Mathematics for Machine Learning” book and strengthen your ML foundations in linear algebra, calculus, probability, and optimization. Download: mml-book.github.io/book/mml-book.… #MachineLearning #MathForML #AI #DataScience #MLBook

Your model’s stuck at a saddle point, and you don’t know it. Learn the Hessian.📘 Pre-order Mathematics of Machine Learning and follow Packt DataPro on LinkedIn. 👉packt.link/OYc5b #MathForML #AI #MLTheory #100DaysOfMathematicsOfML