#matric math notes

[arfan039]

Urdu_10th Class Guess Paper

If you are looking for Urdu_10th Class Guess Paper, you are at right place. Here we have uploaded Urdu_10th Class Guess Paper 2023. We have uploaded Urdu Assessment papers for all important questions, chapters, etc. These questions most often come in BISE Exams. Urdu_10th Class Guess Paper, are equally useful for all boards of Punjab, including Faisalabad, Lahore, Gujranwala, Sahiwal, Rawalpindi,…

[er-cryptid]

Matrix Multiplication - Ex. 2

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[a-moth-to-the-light]

i might have already posted about this a while ago but my favorite ace experience is adapting allosexual terminology for myself (because my friends use it, so i automatically pick it up too) without actually understanding what it means (like i know what it means literally, i just don’t understand the feelings)

what i say: “that’s hot!!” or “oh my GOD that’s so attractive”

what i mean: that is aesthetically pleasing, or it makes me feel safe & happy

what i say: “-5 shots to fuck them”

what i mean: i feel joy about this person!

[strwbi-laces]

so i see your tags on bats post and hm hm hm…

listen. realistically i could see both of them slaying the game in every branch of engineering, and i do respect your opinion. i hold you to the highest regard darling, however you’re incorrect.

you cannot tell me that sirius black - who invented a flying motorcycle for fun - is not absolutely entrenched in mechanical or aeronautical engineering. that bitch is obsessed with machines and moving parts and what comes with that??? physics. she loves physics.

james on the other hand i could see going anywhere. i do like the idea of her being a coding genius but that also feels too boring on its own so let’s give her something chemical or biomedical engineering-y, because you code in all branches of engineering!! i just think that if either of them is going to explode shit, light something on fire, invent bionic arms, it’s her. and she also codes her own games on the side for fun (and because she can sit in sirius’ lap and bounce ideas off of her when she does)

they both work in the same space and the content of engineering overlaps so much that they’re never out of touch with each other. it’s sort of like paralell play, and maybe they fuck up matrices together.

anyways sorry i kinda went off, i have a passion for this topic. i’d love to hear your ideas too <333

Okay fair point about the motorcycle, I did forget about that. I mean you do need chem for that, but yes it’s physics so maybe Sirius does both. I still like the idea of her being walter white tho

ALSO EXCUSE YOU CODING ISNT BORING (it is kinda boring actually but that’s my field i have to defend it).

Jamesy seems like a probability wizz actually. Maybe in ur casino au shes a card counter. Sirius is on her arm watching, knowing exactly what’s going on but she doesn’t really care cause that means james can buy her a drink later!!

OH MY GOD sirius is the dealer, james is a card counter. Thats so hot actually.

Got distracted, anyway james seems like she creates probability algorithms, like a quant, and does game dev on the side. Sirius checks her code and finds the random colon she forgot then holds her while she cries about it.

Okay so, Sirius gets mechanics, James gets statistics and they check each others work and do puzzles together like nerdss <33

[iwanttostudysomething]

◇ 38'th Day of Productivity ◇

10/03/2024

To Do List:-

□ Physics Homework.

□ Revise Matrices.

□ Correct Maths Notebook.

□ Write Psychology Notes.

□ Pratice some questions from English.

□ Read 'Solutions' from Chemistry.

Update:-

Classes actually started on 29'th of February, but I decided to take a break from posting as it would take some time to get used to the more rigorous schedule of 12'th standard.

I finally saw a psychologist today after a long time so let's see how that goes!

I will change the godawful color scheme of this page as soon as I can, lol.

Remark/s 1:-

A bit demotivated today

Remark/s:-

Not bad for being so tired today!

Song of the Day:-

Such a simple composition yet captures so many complex feelings!

[studyyblur]

day 19/100

i'm not really in the mood for a list today, so the study plan for tomorrow is basically to have an overview of all the topics that will be commenced in the upcoming test on this sunday, for both physics and chemistry; with math i wish to start on matrices lecture but only if i'm done reviewing for the test and i'd also continue with my notes on hydrocarbons (i love love LOVE organic chem)

toodles 🤍

[creamsicle-art]

You would think that if someone is showing off the cool Latex formatting on their Stressen's Algorithm notes, it goes without saying that they know what matrices are, and you should not try to explain comp sci 101 level matrix math to them. Yet cishet guys who lurk in college discord servers even though they dropped out constantly surprise.

[pandeypankaj]

What are the mathematical prerequisites for data science?

The key prerequisites for mathematics in Data Science would involve statistics and linear algebra.

Some of the important mathematical concepts one will encounter are as follows:

Statistics

 Probability Theory: Probability distributions should be known, particularly normal, binomial, and Poisson, with conditional probability and Bayes' theorem. These will come in handy while going through statistical models and machine learning algorithms.

Descriptive Statistics: Measures of central tendency, mean, median, and mode, and measures of dispersion—variance and standard deviation—are very important in summarizing and getting an insight into data.

Inferential Statistics: In this part, the student is supposed to be conversant with hypothesis testing and confidence intervals in order to make inferences from samples back to populations and also to appreciate the concept of statistical significance.

Regression Analysis: This forms the backbone of modeling variable relationships through linear and logistic regression models.

Linear Algebra

Vectors and Matrices: This comprises vector and matrix operations—in particular, addition, subtraction, multiplication, transposition, and inversion.

Linear Equations: One can't work on regression analysis and dimensionality reduction without solving many systems of linear equations. 

Eigenvalues and Eigenvectors: It forms the base of principal component analysis and other dimensionality reduction techniques. 

Other Math Concepts

 Calculus: This is not very core, like statistics and linear algebra, but it comes in handy while discussing gradient descent, optimization algorithms, and probability density functions.

Discrete Mathematics: Combinatorics and graph theory may turn out to be useful while going through some machine learning algorithms or even data structures.

Note: While these are the core mathematical requirements, the extent of mathematical background required varies with the specific area of interest within data science. For example, deep machine learning techniques require a deeper understanding of calculus and optimization.

[gawdidklol]

Day 0/7 days of being one step ahead in prep✨

I completed:-

Ioc :- coordination compound notes (CFT<)

Oc:- Reduction notes and shorts notes made only sheet left

Heating effect notes

Maths:- matrices 01

:, not productive

[faurdani]

Neeeerd time!!✨️ (wow it's my 10th months of grad study)

My mood is very good now since today's exam grade is better than I expected alhamdulillah.🤍 so i want to talk about... related to this course: Applied Math I. And other courses actually. I reaaally love that the grad courses connect each other very well!

Actually, this starts from an uneasy feeling I felt in my undergrad. There was a lot of things taught in my undergrad, but I don't understand most of them. And I am very serious. I felt my undergrad is very weird, at least for me. It was so difficult to understand things. I think I did my exams very bad. But the worse thing (to me), is, we did not get any feedback unless the semester is finished.

I hated it because I did not know whether my understanding is correct or not. I didn't know which part is true and which part is not. Whether I did good or bad in midterm, quiz, finals, or homework. I didn't really read the books. I only read Calculus, some Atomic Physics, Feynman for optics & electromagnetics, and books + papers for thesis. Oh, also some parts of book for Sensors, Actuators, Electrical Circuit. The rest.. I just read the prof's ppt/modules. Hahaha ok I admit that I wasn't that "good" in studying.

So I was so lost in Chemistry, Thermodynamics, Heat & Mass Transports, Process Techniques, & Fluid Mechanics. I also felt lost in Linear Algebra, Calculus, Differential Equation, Electronics, Signal Processing, Acoustics, System Dynamics, Controls... (really, I am actually bad... i don't understand how did they grade, why do i still get good grades when I actually don't understand things..)

I might be able to solve the problems from Linear Algebra, Differential Equations, and System Dynamic class back then.

But I didn't understand things. I just followed the pattern, nothing sticked, nothing feels connected.

That's why I was so struggled in the last years of my undergrad: when I faced Instrumentation System Design and Undergrad Thesis--which was about acoustics, mechanics, PDEs.

Many concepts were fixed and got better during the thesis, but I still felt something is missing.

When I first came here (my grad campus), we were tested on 3 subjects, undergrad level: (1) math, (2) physics, (3) chemistry.

Basically that. I passed physics & (surprisingly) chemistry, but failed math, so I should take undergrad level math in my first semester. But I am so happy!

Maybe it's also because I already finished undergrad (so I have some basics, even though it's not strong), maybe the prof is just very good at teaching (the attitude is very great. She is always punctual, effective, and willing to answer every questions. Very helpful). Maybe the ppt, the reference book, the homeworks & quiz are good. Maybe the syllabus, and the curriculum--because at the same time I need to practice a lot of calculus at Fluid Mechanics class. Maybe also the language? I am not so good in English, but now if I think about it... i feel that Indonesian math terms are not intuitive. :") Afterall, maybe it's the combination of that. I love it alhamdulillah. :')

Sooo. In my grad study, I've been taking:

- undergrad math: derivatives, integrals, ODE, series & sequence

- fluid mech: (1) a bit of surface tension, dimensionless analysis, Reynold Transport Theorem, Navier Stokes, vorticity, ideal flow, gravity waves, laminar flow; (2) boundary layer, instability, turbulence, compressible flow (shockwaves); (math) kronecker delta, levi-civita, a looot of PDE & calculus because Navier-Stokes, diff coordinates (cartesian, polar), slight complex for waves & instability discussion

- thermo: 1st, 2nd, 3rd law of thermo; (math) basically PDE *note: i'm still very bad at this*

- solid mech: statics, kinematics, constitutive equations (relating statics & kinematics--basically how to solve/model the solid mechanics phenomenon? --> including elasticity, optimization problem), crack propagation; (math) tensor calculus (dyadic notation, matrices, linear algebra), ODEs, Gauss theorem, diff coordinates (cartesian, cylindrical, polar)

- Applied Math II: complex analysis (complex algebra, derivative, integration, Laurent series) & linear algebra (vectors, dimensions, rank, linear dependency, eigenvalues, eigenvectors. Basically how to solve linear "discrete" system)

- Applied Math I: ODE, PDE. Including Green's Function (transfer function) & Sturm Liouville's problem (eigenvalues, eigenfunctions, linear dependency. How to solve linear "continuous" system)

*phew* that's a lot for one year.

But as you can see... every physics class has some math (generally: calculus, ODE, PDE, linear algebra). It helps me to understand math and math helps me to understand that!

If i remember again, my undergrad has a lot of math also (mainly solving ODE, PDE)..

So that now I'm taking Applied Math I, especially during the Green's function discussion, it blooows my mind!

I rmb very clearly that in undergrad we discussed transfer function *a lot*. It is output per input. But how do we find it?

I didn't understand the math.

In Controls, Acoustics, Instrumentation System Design classes, even for my undergrad thesis, we discussed about harmonic oscillator system.

But i didn't really understand what solution is. Why do we solve that way. Why the transfer function and the solution is written that way.

Now I want to share the main insight from current course. In short (I hope), when we have ODE:

Ly(x) = f(x); L is linear differential operator (e.g. D² + pD + q),

f is the input and y is the output

We can solve this, get a solution of

y(x) = int[ G(x,t)*f(t) ]dt

Such that G, the Green's function is equivalent to output over input; the transfer function. And we practice--G only depends on L and Boundary Conditions!

Moreover,

Ly(x) = f(x) is actually equivalent to

LG(x,t) = delta(x-t); delta(x-t) is impulse at x=t, means we'll get transfer function if we give impulse as the input! (I knew this "physically" but math understanding is ✨️amazing✨️)

And thenn I also just notice (or maybe remember, but now understand by heart, I hope) that impulse is a derivative of step, which is a derivative of smooth piecewise function.

And smooth piecewise function can actually be written as a series. Fourier series.

And Fourier series can also be seen as a linear combination of 3 orthogonal bases: 1, sin(n*pi*x/L), cos(n*pi*x/L). Note that we can imagine 3 orthogonal bases as x,y,z in Cartesian coordinates..

Honestly the concept of relating vectors (matrix, "discrete") with functions ("continuous") amazes me in the beginning of this course. 🥺🥺✨️

[shiva10010]

JEE Main 2025! Prep Your Math Strategy with the Latest Syllabus

The Joint Entrance Examination (JEE) Main is a critical gateway for aspiring engineers in India. While the official syllabus for JEE Main 2025 will likely be released by the National Testing Agency (NTA) in November 2024, you can get a head start on your preparation using the previous year's syllabus as a guide.

This article focuses on the Mathematics section of the JEE Main 2025 exam.

Key Elements of the JEE Main 2025 Maths Syllabus

The JEE Main Maths syllabus covers a wide range of topics from Class 11 and 12 NCERT textbooks. Here's a quick glimpse of the major areas you'll encounter:

Algebra: Sets, relations and functions, complex numbers, matrices and determinants, mathematical induction, binomial theorem, sequence and series.

Calculus: Limit, continuity and differentiability, integral calculus, differential equations.

Geometry: Coordinate geometry, three-dimensional geometry, vector algebra.

Other Quantitative Techniques: Statistics and probability, trigonometry, mathematical reasoning.

Why eSaral is Your Perfect JEE Main 2025 Maths Companion

While the syllabus provides a roadmap, in-depth preparation is essential for success. This is where eSaral steps in:

Complete Syllabus Coverage: eSaral ensures you cover all the essential JEE Main Maths topics.

Detailed Learning Material: Access a treasure trove of resources, including crisp explanations, illustrative examples, and topic-wise revision notes [refer to JEE Main 2025 Maths Revision Notes on eSaral for details].

Catered Learning Styles: Whether you prefer short and focused content or a deep dive into concepts, eSaral offers options to match your learning style.

Practice Makes Perfect: Sharpen your skills with ample practice problems available on the platform.

Additional Tips to Conquer JEE Main 2025 Maths

Focus on NCERT Textbooks: They form the foundation for the entire syllabus.

Regular Practice: Solve problems consistently to build speed, accuracy, and exam temperament.

Mock Tests: Take regular mock tests to simulate the exam environment and identify areas for improvement.

Clear Your Doubts: Don't hesitate to seek clarification from teachers or online forums.

Conclusion

JEE Main 2025 Maths can be aced with the right approach and resources. By leveraging the detailed syllabus and comprehensive learning materials offered by eSaral, you can approach the exam with confidence and a strategic plan. Remember, consistent effort and focused practice are key to achieving your engineering dreams.

[er-cryptid]

[usaq22]

(1) March 2024 Journal (Joniaux).

(2) Table of Contents =

Table of Contents. (Newest iMAGE Search All iNTERESTiNG Words!).

Welcome to March 2024! (48/671 MiT Calculus).

Picture Folder Organization.

Wolfram|Alpha: Entering iNPUT Math Student iNTRODUCTiON.

Wolfram|Alpha: Managing Computations iN NoteBooks. 

Large Language Model Programming.

Get Code Definitions by Highlighting & Option Clicking.

Wolfram|Alpha: Free-Form & External iNPUT.

Kinetic Learning Types.

Note On “Accordion Style” (Collapsible List) Format.

Fractions & Decimals (Wolfram|Alpha).

Variables & Functions (Wolfram|Alpha).

Algebra (Wolfram|Alpha).

Plots iN 2D (Wolfram|Alpha).

Geometry (Wolfram|Alpha). 

Trigonometry (Wolfram|Alpha).

Polar Coordinates (Wolfram|Alpha).

iF > Documentation Search [SingleWord] ⮚Then > Return “SubjectWordList” 1st [Before Singular Word Definitions’.

Exponentials & Logarithms (Wolfram|Alpha).

Limits (Wolfram|Alpha).

Derivatives (Wolfram|Alpha).

Integrals (Wolfram|Alpha).

Trace and Zoom (MiT 48/671).

Sequences, Sums, and Series (Wolfram|Alpha).

Recursive Sequence (Google).

Recurrence Table (Wolfram|Alpha).

Wolfram|Mathematica Documentation Center WebPage Suggestions:

A Note About “LinkLines”.

March 7th 2024.

More Plots iN 2D (Wolfram|Alpha).

Plots iN 3D (Wolfram|Alpha).

MultiVariate Calculus (Wolfram|Alpha).

Vector Analysis & Visualization (Wolfram|Alpha).

Differential Equations (Wolfram|Alpha).

Ordinary Differential Equation [ODE] (Google).

Partial Differential Equation [PDE] (Google).

Delay Differential Equation [DDE] (WikiPedia). 

iNTERPOLATE (Oxford).

iNTERPOLATiNG Function (Google).

Parametric (Dictionary.Com).

Product ∏ Notation (WikiPedia).

Learning Algorithm (Joniaux).

CoProduct ∐ Notation (WikiPedia).

Complex Analysis (Wolfram|Alpha).

Matrices & Linear Algebra (Wolfram|Alpha).

Discrete Mathematics (Wolfram|Alpha).

Probability (Wolfram|Alpha).

Statistics (Wolfram|Alpha).

Data Plots & Best-Fit Curves (Wolfram|Alpha).

Group Theory (Wolfram|Alpha).

Math Puzzles (Wolfram|Alpha).

iNTERAVTiVE Models (Wolfram|Alpha).

Mathematical TypeSetting (Wolfram|Alpha).

Color Text iS Necessary for Documentation, but NOT for Note Taking (Joniaux).

Chapter 2: Derivatives (MiT) — 2.1 The Derivative of a Function.

The Derivative of [1/t] (Mit).

2.2 Powers and Polynomials (MiT) [57/671].

Derivatives of Polynomials (MiT) [59/671].

A Look at Differential Equations (Find [y] from [dy/dx]) {MiT} <60/671>.

Marginal Cost and Elasticity iN Economics (MiT) [61/671].

iT Was Books, but Now  iT iS Simulators, Computers, and Programs (Joniaux).

2.3 The Slope and the Tangent Line (MiT) [65/671].

The Equation of a Line (MiT) [65/671].

March Summary (Joniaux).

[vasanthasworld]

WBCHSE Solutions For Class 12 Maths Algebra

[vijayadworld]

WBCHSE Solutions For Class 12 Maths Algebra

[richtong1]

pod: rt3. AI Hardware Introduction

This is another sort of nerdy side note. If anyone is still watching, this section is just to give intuition on the basics of the hardware. There are lots of assumptions about GPUs and CPUs that I wanted to make sure people understood. But the basics are that CPUs are tuned for lots of branches and different workflows, while GPUs are tuned for lots of the same things like matric math. And…