#mathforml zoekresultaten
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
Math for ml day 3 Today i've learned math induction, and now i'm going to learn trigonometry #mathforml
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
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
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
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
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
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
Build a strong foundation in #Mathematics for ML with Coursera's Mathematics for Machine Learning coursera.org/specialization… or MIT OpenCourseWare's Mathematics for Computer Science ocw.mit.edu/courses/electr…. Understand linear algebra, calculus, and probability theory. #MathForML
ocw.mit.edu
Mathematics for Computer Science | Electrical Engineering and Computer Science | MIT OpenCourseWare
This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides roughly into thirds: 1. Fundamental Concepts of Mathematics: Definitions,...
🚀 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
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
youtube.com
YouTube
Symmetric Matrices and the Positive Definiteness
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
📘 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
Overview of data distributions disq.us/t/3pg0vra . Probability distributions- always find them a challenging topic. Wish I had this before. #Stats #Probability #MathforML
📘 Today in my AI journey: Diving into Linear Algebra basics 👉 🔹 Linear Combination 🔹 Bias 🔹 Span These are the building blocks for understanding ML models & neural networks. Excited to keep learning & sharing! 🚀 #AI #MachineLearning #MathForML #LinearAlgebra
Matematika itu indah. Di balik setiap model ML ada logika elegan dari matematika. Jangan menghindarinya, taklukkan ia! Ini adalah superpower rahasiamu. 🧠✖️ #MathForML #Algorithm #Logic
📘 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
youtube.com
YouTube
Symmetric Matrices and the Positive Definiteness
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
youtube.com
YouTube
Mathematics for Machine Learning [Full Course] | Essential Math for...
✨ 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
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
📏 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
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 🧠💪
🚀 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
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
Making a tree-diagram cheat sheet for probability counting problems. 🤗 First leaf: The multinomial Coefficient #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
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
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
Matematika itu indah. Di balik setiap model ML ada logika elegan dari matematika. Jangan menghindarinya, taklukkan ia! Ini adalah superpower rahasiamu. 🧠✖️ #MathForML #Algorithm #Logic
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
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
Before ChatGPT, there was calculus. The Jacobian powers backprop - math is the original pre-training. 📘 Pre-order Mathematics of Machine Learning + follow Packt DataPro on LinkedIn for more.👉packt.link/OYc5b #MathForML #AI #MLTheory
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