Sharing my perspectives on various topics (from IIT Madras in Data Science students forum).
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Need help with avoiding procrastination:
Very good.
You are aware of your problems. I am sure that there equal number of students doing the same thing as you but not aware, blaming others for not achieving.
You are making significant progress.
Pick any subject that interests you. Love it sincerely.
Investigate everything in that subject. You must have very clear understanding of that subject.
Fundamental concepts are the same.
From the conceptual clarity you get from the subject of your choice, you can map the the other ideas of other subjects.
I have used Ohms law to calculate external debt (while solving economic problem).
See that coming up in Problem 13 of Week2 Mathematics.
It appears as Law of Total probability in statistics.
It has danced in chemical reaction equations ( remember the balancing problem) ?
It is there every where. Science is not an abstract subject away from you. Science is an attempt to explain how we are living.
Remember the Boyle’s law ? when did you last use it ? (you thought it was worth 2 marks in your 12th!)
Take a deep breadth.
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While solving GrPA05 in Week1 (python), after coding( in PyCharm), I asked my daughter to check with different inputs to ensure the ruggedness.
When she reported an error, I could not stop laughing because of an old incident, which is worth sharing here.
In the year 1974, after relinquishing the office of President of India, Shri V.V.Giri visited Ramco, in Madras. My friend TV Krishnamoorthy was a programmer (who had a keen interest in astrology) had developed a code to print the “horoscope” of individuals. Obviously , the Chairman of Ramco, showcased the new computer and asked the horoscope of Shri Giri be printed.
The system crashed and much later, it was found that the year field used in the code was two digits ( to save the memory, that was common in those days) and Shri Giri’s birth year being 1894, it failed to print the horoscope of a person not yet born in 1974.
(74 - 94 = negative).
That was the first time, we, bunch of guys in the Beasant Nagar beach wondered the possible impact of Y2K issue.
The same Y2K which put India in front of the world as savior in need.
The GrPA05 in Week1 also had only two digits for year and when my daughter put my birthday, it gave an error !
History repeats in funny ways.
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Rise of new-age technology—specifically AI and machine learning
Whenever new tool based on emerging technology is introduced, it is intimidating.
I have seen accountants skepticism when electronic calculators were introduced, I vividly remember the arguments from charted accountants questioning the accuracy of calculators,
Later, it was computers. Remember the resistance from unions in 1980s ?
Some you will know the whole lot of ‘stenographers’ who were replaced by word processors ?
The cashiers in large companies who spent enormous amount of time to compute the workers salary ?
Yes, when a new technology arrives, all the people have to upgrade themselves to use the new technology. We can not be static, when everything around us evolve continuously.
The sheer number of students ( above 40 years) enrolled in this program itself is a proof.
May be it is time to upgrade the skill set of ‘typical coders’. They have to evolve to become analysts and system architects.
Nothing ever remains the same. Change is inevitable. Adoption is the only way to survive and evolve.
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How long for results of quiz 1
Indulge, if you will, in a fleeting interlude of unrestrained and perhaps quixotic optimism, a period wherein the mind revels in unbridled conjectures of success, untainted by the oppressive finality of empirical outcome—until, alas, the inevitable verdict descends with unceremonious veracity, poised to shatter the delicate equilibrium of your ephemeral euphoria
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It was a few days before Pongal, on January 12, 1976, the night before the largest rocket to date was set for testing. After intense preparations, which were nearly complete, I stepped out of the bunker to take in some fresh air and joined a small group chatting on the shores of the Bay of Bengal.
Khan, the chief of mechanical engineering, visibly exhausted from managing the massive rocket, asked Dr. Kalam, “As technology advances, we’ll be building rockets with much greater width. Perhaps we should consider setting up a new test bay with facilities to accommodate wider designs.”
Dr. Kalam seized the opportunity to share some historical context about the practical limits on rocket width. In his characteristically steady tone, he explained, “You see, in the U.S. and Russia, rockets are developed at multiple facilities and transported by rail. Since the rockets must fit on railway wagons, their width can’t exceed the railway tracks. The track width itself is based on the spacing of wheels on horse-drawn carriages, which aligned with horses for better traction. So, there’s a historical limit on how wide a rocket can be.”
Upon hearing this, T.N. Sheshan, then the Officer on Special Duty, exclaimed, “I never knew the upper limit of our rocket size was determined by a couple of mules’ backsides!”
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Is it risky to pursue this IITM degree standalone?
Is there anything without risk ?. If it is, will it be worth ?
Remember this old song:
When I was just a little girl
I asked my mother, what will I be
Will I be pretty? Will I be rich?
Here’s what she said to me
Qué será, será
Whatever will be, will be
The future’s not ours to see
Qué será, será
What will be, will be
When I grew up and fell in love
I asked my sweetheart what lies ahead?
Will we have rainbows day after day?
Here’s what my sweetheart said
Qué será, será
Whatever will be, will be
The future’s not ours to see
Qué será, será
What will be, will be
Now I have children of my own
They ask their mother, what will I be
Will I be handsome? Will I be rich?
I tell them tenderly
Qué será, será
Whatever will be, will be
The future’s not ours to see
Qué será, será
What will be, will be
Qué será, será
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The Universe is hostile to computers
Hey,
Trillions of bits flip every moment. All the time. We know it.
some will fail to flip the way we expect, wrongly and will be explain it by error rate , statistical behavior, etc. No one expects that all the bits will flip always the way we want.
The problem is which bit fails. Least significant or most significant. What is least significant to me may be most significant for some one else.
We choose to attach importance to what we want.
sometimes we choose to make story out of it.
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The problem descriptions are not complete which leads to errors
Graded assignments, quizzes, and tests ain’t just routine chores—they’re lively skirmishes where two sorts of players square off. On one side, you’ve got the students, not exactly sitting around idle, but straining their brains to come up with the right answers. On the other, the teachers, who aren’t simply dishing out questions but honing the fine art of asking the tough ones. It’s a back-and-forth affair, and as these skirmishes keep cropping up, neither side walks away without gaining a bit more skill, whether they’d intended to or not.
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Observing the plight of all those still waiting for house allotments from IITM, I decided to consult Nastur Daruwalla, the son of the renowned astrologer Bejan Daruwalla, to ask when the allocation might happen. He explained that Jupiter, the planet governing dwellings, is currently retrograde, and once it resumes its direct motion, the allotments would likely proceed.
Hearing this, my daughter, who is pursuing her Master’s in Machine Learning, couldn’t resist teasing me for relying on such beliefs. I responded with a smile:
'Think about it—aren’t we all trying to predict the future in some way? We analyze vast amounts of past data, searching for patterns to help mitigate future uncertainties. Whether it’s modeling the world to predict a product’s success, the outcome of an election, or the best strategy for a company’s growth, we’re doing exactly what fortune-tellers have done for centuries.
In the old days, people turned to astrologers, tarot readers, or even parrots to make sense of the unknown. Today, we rely on Naive Bayes Classifiers, Decision Trees, Random Forests, Support Vector Machines, Neural Networks, Clustering Algorithms, and Deep Learning. While the tools and terminology have evolved, the fundamental goal remains the same: predicting the future.
Like it or not, we are modern-day ‘Jyotishis,’ fortune-tellers in suits and ties, armed with algorithms instead of astrology charts.’
My daughter couldn’t help but laugh, but I think I made my point.
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As aspiring data scientists, we constantly seek to uncover patterns in the data around us, revealing the truths hidden beneath the surface. Many of us are already familiar with algorithms like Breadth-First Search (BFS) and Depth-First Search (DFS). In these algorithms, we maintain a record of previously visited nodes to avoid falling into endless loops—a fundamental concept that extends beyond programming.
History, in a similar sense, is a collection of past events (or nodes). Understanding history helps us avoid repeating mistakes and prevents us from getting stuck in “infinite loops” of human error. Knowing where we’ve been is essential to knowing where we’re headed.
Most students on this data science journey have grown up in the internet era. For them, life without smartphones, the internet, computers, or calculators is unimaginable. However, there are seasoned professionals with rich, pre-digital experiences.
I encourage these veterans to share their stories, enriching the perspectives of those newer to this planet and this profession.
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Tomorrow is the big day! Your Python test is not just a challenge—it’s an adventure. Think of it as debugging your way through the jungle of syntax, logic, and creativity. You’ve got this!
Remember, Python doesn’t bite (unless you forget your indentation!). When in doubt, think like Python: simple, elegant, and always ready to solve problems. Treat your code like a good recipe—keep it clean, follow the steps, and don’t forget to test your flavors (or outputs )!
Some tips for tomorrow:
Stay calm: If you see an error, don’t panic—errors are just Python’s way of saying, “Try again, you genius.”
Trust your training: You’ve practiced loops, conquered conditions, and mastered functions. You’re the hero of your own Python script.
Import confidence: It’s your most powerful library. (But don’t actually try import confidence—it’s not a real module… yet. )
And hey, even if you find yourself staring at a tough question, remember: life is like Python—sometimes you just have to pass and move on to the next one!
Good luck, coders! May your outputs be accurate, your logic be solid, and your coffee be strong. Go crush it!
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Ed Furgol, the professional golfer, once quipped: “My luck is so bad that if I bought a cemetery, people would stop dying.” Every time I attempt to master a new programming language, I can’t help but think of his words.
My computer journey began in 1974 with BAL (the assembler code for IBM 360), which I used to simulate an HP 1000 mini-computer. That marked the beginning of a lifelong tango with ever-changing technologies.
By the late '70s, RPG and COBOL were the talk of the town, making transitions to most mini-computers easier. BASIC soon followed, and I still remember the linear programming model I wrote for Dr. B.V. Rao to optimize chicken feed nutrition. That work eventually helped shape the hatchery business of Venky’s Chicken—a feather in both their cap and mine.
The early '80s saw me diving deep into Intel’s 8085 assembler, only to be blindsided by the emergence of C and C++. Just as I wrapped my head around the intricacies of object-oriented programming, Java ascended to dominance, demanding my attention.
Simultaneously, the internet birthed a deluge of client-side scripting languages, each clamoring for relevance. By 2010, as I found comfort in Google Script and Visual Basic, along came R to save the day with its prowess in handling vectors.
And now? Now I find myself wrestling with the new reptile in town: Python. Taming this beast has proven to be an uphill battle, but if there’s one thing I’ve learned, it’s that technology waits for no one. When you’re in the business of taming technology, you must adapt to the language of each new beast.
But Python won’t be the final chapter. As new technologies emerge, so too will new languages, each with their own demands. And so, the cycle continues, reminding me that the journey—not the destination—is what makes it all worthwhile.
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I’ve done the calculation and your chances of winning the End Term are identical whether you
worry about it or not.
Stay Calm and Confident
Practice relaxation techniques to manage stress.
Maintain a positive attitude, believing in your preparation.
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I often see students stressed about the weightage of various portions in exams. As someone who has faced numerous tests in the past, I wanted to share a perspective on behalf of my fellow students.
The purpose of studying a subject is not merely to score well but to gain knowledge, understand new methods, and grasp concepts that will prove useful throughout life. Tests conducted by institutes are simply tools to help us identify what we might have missed during the learning process. They are part of the journey, not the destination.
The real tests come later, in life. It might be when you’re persuading a client to believe in your ideas, convincing a minister to allocate land for your project, or measuring a critical parameter under challenging conditions. These challenges will arise time and again, and the concepts you learn now will support you when you need them most.
So, don’t let scores dominate your focus. While they hold importance, they are not the only measure of your potential. Be confident in what you know, and stay aware of what you still need to learn. The process of learning never truly ends. There have even been times when I’ve learned something new during an exam!
Remember, a lack of confidence can cloud your mind and hinder your ability to recall what you already know. Trust yourself, embrace the process, and approach every test—whether academic or in life—as an opportunity to grow.
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How to grow gracefully ? A taunting thought of mine was answered recently when I came across this piece. Thought of sharing for the benefits of souls in similar boat.
Fabulous Message
All Fused Bulbs are the Same !
A senior executive retired and shifted from his palatial official quarters to the housing society, where he owned a flat. He considered himself big and never talked to anyone. Even while walking in the society park every evening, he ignored others, looking at them with contempt.
One day, it somehow transpired that an elderly person sitting beside him started a conversation, and they continued to meet. Every conversation was mostly a monologue with the retired executive harping on his pet topic, Nobody can imagine the big post and high position I held before retirement; I came here due to compulsions”; and so on, and the other elderly person used to listen to him quietly.
After many days, when the retired executive was inquisitive about others, the elderly listener opened his mouth and said, After retirement, we are all like fused bulbs.
It does not matter what a bulb’s wattage was, how much light or glitter it gave, after it gets fused.
He continued, “I have been living in this society for the last 5 years and have not told anyone that I was a Member of the Parliament for two terms. On your right, over there is Vermaji, who retired as General Manager in Indian Railways. Over there is Singh Saheb, who was a Major General in the Army. That person sitting on the bench in spotless white dress is Mehraji, who was the chief of ISRO before retirement. He hasn’t revealed it to anyone, not even to me, but I know.”
All fused bulbs are now the same – whatever its wattage was – 0, 10, 40, 60, 100 watts – it doesn’t matter now. Neither does it matter what type of bulb it was before it got fused – LED, CFL, Halogen, Incandescent, fluorescent, or decorative. And that, my friend, applies to you too.
The day you understand this, you will find peace and tranquillity even in this housing society.
The rising sun as well as the setting sun are both beautiful and adorable.
But, in reality, the rising sun gets more importance and adoration, and is even worshipped , whereas the setting sun is not given the same reverence. It is better to understand this sooner than later. Our current designation, title and power are not permanent.
Keeping lot of emotions with these things only complicate our life when we lose this one day.
Remember that when the game is over, the king and the pawn go back in the same box.
Enjoy what you have today . Have a fabulous time ahead….
At the end of the day all those certificates are replaced by only one certificate… death certificate
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Some of you may not have met the passing criteria for a subject this term. To encourage you, I’d like to share a personal story.
In 1968, when I joined engineering college, I had big aspirations, just like any other student. My goal was to graduate with Honors, the highest distinction at the time. To achieve Honors, one had to pass all 10 semesters on the first attempt, maintain an average of over 75% up to the 8th semester, and take two extra subjects, also scoring above 75% in all.
However, my dreams took an early hit when I failed English in the very first semester. Having studied in a vernacular medium until the 11th grade, I struggled and was deeply disappointed. But looking back, it was the best thing that could have happened to me.
That failure forced me to reflect. I realized I had been treating language as something to be memorized, rather than understood. I used to think English had no logic—just a set of grammar rules to cram. Once I shifted my mindset and began analyzing the rules, English became much easier to learn and master.
I’m grateful to those who helped me correct my approach early on. It not only allowed me to conquer English but also prepared me to face many more challenges in life. By the 9th semester, the university revised its rules, enabling me to take the extra electives and achieve my dream of graduating with Honors.
The lesson here is simple: identifying your weaknesses early in life is a gift, not a setback. Don’t let failure discourage you. Reflect, find what you need to improve, and work on it. Every failure is an opportunity to grow
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After three days of intense meditation, I returned to the material world and learned something intriguing from my daughter. She told me about a peculiar belief held at her university, NYU. According to her, no student dares to walk under the iconic Washington Square Arch. The superstition claims that doing so would prevent them from graduating within four years.
This curious anecdote reminded me of a story I once heard from a friend, long ago:
In a remote village in Tamil Nadu, there lived a priest with his daughter and a black cat. After becoming a widower, the priest dedicated himself to performing rituals and ceremonies for the villagers, who relied solely on him for their religious needs.
Before conducting a homam (a sacred fire ritual), the priest followed a strict routine. He would ask his daughter to bathe in the backyard stream and bring water for the ritual. She also prepared other materials and was familiar with the entire process. One peculiar detail stood out: just before starting the homam, the priest would always instruct his daughter to tie the black cat to a post.
Years later, the priest passed away, and during the mourning period, the black cat also died. When the villagers, finding no one else capable of performing the rituals, turned to the priest’s daughter, they believed she knew all the rites by heart.
As she prepared for the homam, she suddenly insisted on having a black cat to tie to the post. Unbeknownst to her, her father’s original purpose for tying the cat was simply practical—to keep it from causing disruptions during the ceremony.
This story offers a profound lesson: rituals are often born from practical purposes, yet their true meanings can fade over time, leaving only blind adherence to tradition.
Reflecting on the superstition at NYU, I wondered if it could be linked to an ancient Roman custom. The Romans had a practice where, upon the completion of an arch, the engineer responsible for its construction stood beneath it as the capstone was set in place—an act symbolizing ultimate accountability for their work. Could this old tradition echo faintly in the modern superstition of avoiding the arch?
Every formula we have learned in this course is rooted in a wealth of underlying concepts. Let us remember these foundational ideas and avoid applying the formulas blindly.
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I write this with utmost respect and a humble request to kindly escalate this matter to the appropriate level for resolution.
As students of this course, we are united in our mission to build a better nation equipped to face the challenges of the digital world. It is said that intelligence is the ability to adapt to changing environments, and we, too, must adjust our actions when circumstances evolve.
However, the current system at IITM continues to send repeated emails urging students to join the course—even to those who have already completed all formalities, including fee payment. This raises concerns about the credibility of our institution, especially when we aim to teach advanced topics such as artificial intelligence.
A fundamental principle in digital communication, particularly in marketing, is targeting the right audience. Overlooking this essential aspect undermines our efforts and sends a contradictory message about our capabilities.
I kindly urge the concerned team to address this issue by implementing appropriate filters to ensure such reminders reach only those for whom they are relevant. This small yet significant improvement will not only enhance the efficiency of our communication but also reflect our commitment to the principles we teach.
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Throughout this course, we have encountered numerous formulas and crunched countless numbers to arrive at solutions.
However, most of us may have overlooked a seemingly trivial yet crucial point: each symbol we use represents a physical quantity in the real world. Any measurement is incomplete without its corresponding unit of measurement. Yet, more often than not, we tend to ignore its significance.
An incident buried in the euphoria surrounding the dawn of the new millennium (December 31, 1999) comes to mind—a time when I had the opportunity to participate in a system audit.
The Mars Climate Orbiter was launched by NASA on December 11, 1998.
The spacecraft traveled for about 10 months to reach Mars and was scheduled to enter orbit around the planet on September 23, 1999.
The navigation team at NASA’s Jet Propulsion Laboratory (JPL) used the metric system (newton-seconds for force and thrust calculations).
The engineering team at Lockheed Martin, who built the spacecraft, used the imperial system (pound-seconds).
The mismatch meant the spacecraft’s navigation software received incorrect data about the thrust applied to the spacecraft.
Over the course of the mission, the incorrect unit conversion caused the spacecraft’s trajectory to deviate.
By the time the Mars Climate Orbiter reached Mars, it was flying far closer to the planet’s surface than intended—57 kilometers (35 miles) instead of the planned 150 kilometers (93 miles).
Different teams worked in isolation (usual in large projects - required for secrecy issues), and the importance of unit consistency was overlooked.
The Mars Climate Orbiter crash showed that in complex systems, small errors—like mixing up pounds and newtons—can lead to enormous failures.
Next time you solve a problem, take a moment to reflect: does the unit (or dimensionality) pass the sanity check?
For instance:
Does the power of exponentials in a Gaussian distribution effectively cancel out the units, as it should?
What about the expressions within the brackets of sine and cosine functions—are they truly unitless, as required by trigonometric principles?
These subtle considerations often go unnoticed but are essential to ensure the correctness of your calculations.
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Many of us frequently solve problems of the form Ax=b in science and engineering, often simply because our teachers ask us to. But if we take a moment to reflect, we should ask ourselves:
What does Ax really mean?
We know that x is a vector, and when the matrix A operates on it, the result is another vector.
Now, let’s try to understand the relationship between the original vector xxx and the transformed vector Ax.
The transformation can only do two things:
Change the direction of the vector.
Change its length (scale it up or down).
These changes occur due to the numbers in the matrix A.
Now, consider these fundamental questions for any given matrix A:
Are there any vectors that get “killed” by A?
That is, are there vectors for which Ax=0? If so, how many such vectors exist? The collection of all such vectors is called the null space of A.
Are there any vectors that do not change direction when A acts on them?
If a vector only scales (shrinks or expands) but retains its direction, we call it an eigenvector of A. The factor by which it scales is called the eigenvalue. Eigenvectors are special because they remain “immune” to the directional effect of A, experiencing only a change in magnitude.
Understanding these properties helps us grasp how a matrix A behaves when applied to a vector.
Why Do We Care About Matrices?
Because real-world data—observations, measurements, and systems—can often be represented as matrices.
Think of an unknown black box: if we have no information about it, how do we figure out its behavior?
We apply different stimuli, observe its responses, and analyze how it reacts to various inputs.
Similarly, to understand a real-world system represented by a matrix A, we study how it transforms various known vectors. This gives us a feel for how it might behave when applied to new inputs.
And that, in essence, is the foundation of data science.
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I agree with Anupam.
I find that here in this course, IIT can not completely ‘teach’ all the concepts to the required depth. ( due to the ambitious short duration).
However, they excel in coming with challenging questions which will test and reveal what we missed out in learning and help us to pick up ( from elsewhere or any where).
Knowing what we assumed to be known itself is a great way of learning.
I enjoy knowing how stupid I was till a tough question dances in front of me.
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Why Dijkstra fail if there are negative weightages in the graph ?
Imagine choosing a career path:
Dijkstra (Short-Term Thinking)
You pick a job that offers the highest salary right now, without considering long-term career growth.
Later, you realize a different job (which seemed less attractive at first) would have led to a much better future.
You can’t go back because you’ve committed too much already.
Bellman-Ford & Kruskal (Long-Term Thinking)
You evaluate multiple career paths over time, adjusting based on new information.
Even if an opportunity looks bad right now, you keep checking until you find the best overall path.
That is why Dijkstra fail if there are negative weightages in the graph.
Unseen fortunes become unrealized.
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Consider the following passage:
So, basically, what I’m trying to say here is that, you know, when you look at the way people go about saving money—like, you know, putting aside cash for emergencies or whatever—it’s kind of crazy how many people don’t actually do it, even though everyone knows it’s important, right? I mean, think about it, if something unexpected happens, like your car breaks down out of nowhere or your phone, which you totally rely on every single day for like everything, suddenly stops working, then you’re in trouble if you don’t have some cash set aside. And, you know, a lot of folks, they keep saying they’ll start saving soon, maybe next month or next year, but somehow, it never really happens because there’s always something else to spend money on, like eating out or getting that new thing that’s on sale. Anyway, at the end of the day, the point is, people should really think about saving, even if it’s just a little bit at a time, because, you know, life is unpredictable and stuff happens, and if you’re not prepared, well, then it’s just gonna be a huge mess, you know?
Now, if you analyze, it essentially says the following:
Many people know they should save for emergencies but don’t actually do it. When unexpected expenses—like car repairs or a broken phone—arise, they struggle without savings. Despite good intentions, spending on non-essentials often takes priority. Even small, consistent savings can help, because life is unpredictable, and being unprepared can lead to financial trouble.
In English classes, we learned precise writing—the art of removing clutter.
In electrical engineering, it’s called signal processing.
In corporate communication, it’s a synopsis.
In communication engineering, it’s data compression.
At its core, the goal is to eliminate the unnecessary, making the message more manageable.
In data science, we extract essential information from noisy raw data. The key technique is identifying what is fundamental—the core information from which all other details can be derived. Mathematically, this concept is represented by eigenvectors, which form a basis for reconstructing the whole system.
When we structure data in a matrix, we seek eigenvectors to uncover its fundamental components. Essentially, diagonalization and Singular Value Decomposition (SVD) are mathematical analogs of precise writing—retaining the essence while discarding the excess.
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Certain cognitive processes and neural functions exhibit hemispheric lateralization, meaning they are more dominant in one hemisphere than the other.
Left Side of the Brain (Logical & Analytical)
The left hemisphere governs logical reasoning, critical thinking, mathematical and analytical skills, and sequential processing (step-by-step thinking). It relies on established knowledge, seeks conformity to past patterns, and assumes that historical trends predict the future—principles that form the foundation of Data Science.
Right Side of the Brain (Creative & Intuitive)
The right hemisphere is responsible for Intuition, and holistic thinking. It thrives on breaking patterns, exploring the unknown, and challenging conventional wisdom. Most of the management subjects fall under this , allowing us to go beyond what what is presented. Encourages different perception and interpretations. BDM, BA as a consequence do not have unique answers and can not be tested objectively.
I’ve often observed these orthogonal skills in conflict within various professional groups—developers and delivery heads rigidly adhering to rules, while sales teams champion disruption in the name of “customer choice”; auditors demanding compliance, while investment managers push for innovation to maximize returns.
Even at IITM, this tension is evident when we attempt to teach both logic and concepts that transcend logic. A perspective that resonated with me comes from a renowned classical musician, offering a thought-provoking way to understand this conflict—one that is certainly worth exploring.
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There are many concepts to learn in Data Science. We gather inputs from lectures, notes, and peer discussions. What we extract from this knowledge is tested through AQs—our training data. We then validate our understanding against GA, which serves as our validation data. Finally, the concepts that survive this filtering process are tested in the final exam.
Most courses use AQs and GA to train and validate our understanding, allowing us to refine our concepts. This approach falls under supervised learning, where we receive feedback to correct our mistakes.
However, for the sake of completeness, some programs—such as BDM—follow an unsupervised learning model. Here, we are provided only with raw data, with no direct feedback. We keep learning, but there is no clear way to determine whether our understanding is correct or incorrect.
Perhaps this method reflects a deeper truth: in the real world, there are no absolute “right” or “wrong” labels—only perceptions and interpretations.
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Confusion arises from awareness—an understanding that multiple possibilities exist and uncertainty in choosing the best one. On a freeway with no junctions, the absence of choice lets the mind rest. But when choices appear, so does uncertainty.
In moments of confusion, we recognize that the options before us may not be the only ones and that our evaluation method may be flawed. It signals the need to refine our reasoning or reconsider overlooked alternatives.
Far from being a weakness, confusion is the first step toward growth. Deep thinking and exploration sharpen our understanding, leading to greater clarity.
I embrace confusion—but in moderation. Left unchecked, it breeds doubt, eroding conviction until it consumes us entirely.
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You can compare precision vs. accuracy to DFS vs. BFS in an interesting way:
Depth-First Search (DFS) → More Precise, Less Accurate
DFS explores deeply in one direction, focusing on specific paths. This is like being precise—sticking to a narrow focus—but you might not find the correct (accurate) solution if you go down the wrong path.
Breadth-First Search (BFS) → More Accurate, Less Precise
BFS explores broadly, covering all possibilities layer by layer. This increases accuracy since you’re more likely to find the correct solution but at the cost of precision because you are searching everywhere.
So, if you want high precision, you focus deeply and limit your search area (like DFS). If you want high accuracy, you explore broadly but may lose precision (like BFS).
Prudence settles down for a balance between these conflicting traits !
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A teacher is someone who has read the book before you, understood the topic, and genuinely wants to share that knowledge with you.
The ability to simplify complex concepts is a rare and valuable skill—one that only a few have truly mastered.
Beyond explaining concepts, one of the most important responsibilities of a teacher is identifying where we misunderstand things and pointing out our errors so we can correct them. This step is crucial for deep comprehension. A common method for this is testing, which, unfortunately, is often seen merely as a hurdle to clear for certification, rather than as a valuable learning tool.
Imagine you are an athlete training for the Olympics. If your coach only tells you that you are doing great all the time, will you succeed? Shouldn’t they instead point out your mistakes so you can improve? The best coaches are willing to do this, even when it is uncomfortable.
However, the fear of causing discomfort often holds teachers back from being critical. This is why many parents struggle to teach their children skills they excel at—they love them too much to criticize. Ever heard of a math professor’s child failing math? It follows the same logic.
As students, our focus should be on understanding:
What is being taught?
Why is it important?
When can I use it?
Instead of worrying about how much weight a topic carries in the final exam, we must remember—the ‘End Term’ is not the end. In real life, you never know which knowledge you might need, or when.
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Have you ever noticed — no theory truly begins from nothing. Every doctrine, every explanation, starts with an axiom: a foundational assumption, an article of belief we accept without proof. It lies outside logic, beyond questioning, not because it’s irrefutable — but because we choose to treat it as the ground from which all else can grow.
We are taught to “believe” these axioms — not to prove them, but to trust them. Upon these initial leaps of faith, logic constructs vast architectures. One layer supports the next, and those “superstructures” give rise to even more complex frameworks — “super-superstructures,” if you will — until eventually, we declare: We understand.
But what is this process, really?
Is learning just the act of finding the missing links between ideas we’ve already agreed to believe in? Is it the acceptance of new connections as long as they don’t threaten the foundations we’ve inherited?
And so the question deepens:
Do we ever truly learn anything new?
Or are we simply wandering the corridors of an already-built palace, discovering rooms we hadn’t noticed before — rooms built atop assumptions we never laid ourselves?
Is there anything new to learn — or only new ways to believe?
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Recently this is what I said to someone about GPA :
'Your brother is right about GPA. You should aim for 9 at foundation level, as it will be increasingly difficult in diploma level to get higher scores to lift it up. It is always true that the width of the tower decreases as the height increases.
Repeat, if necessary those foundation subjects to maximize your GPA. At diploma level, the TA sessions will not help you to grasp the concepts. They will just defend what they are doing. You will be largely on your own.
Also, having a strong foundation will help you to stand on your own in diploma /degree level. Don’t be afraid to repeat whichever subject that you think can help you to improve your GPA. I have many posts in this forum, search and read them to get motivated to see the importance of strong foundation and clarity of concepts.
Best wishes ! Be brave and fight it out.’
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I often see students stressed about the weightage of various portions in exams. As someone who has faced numerous tests in the past, I wanted to share a perspective on behalf of my fellow students.
The purpose of studying a subject is not merely to score well but to gain knowledge, understand new methods, and grasp concepts that will prove useful throughout life. Tests conducted by institutes are simply tools to help us identify what we might have missed during the learning process. They are part of the journey, not the destination.
The real tests come later, in life. It might be when you’re persuading a client to believe in your ideas, convincing a minister to allocate land for your project, or measuring a critical parameter under challenging conditions. These challenges will arise time and again, and the concepts you learn now will support you when you need them most.
So, don’t let scores dominate your focus. While they hold importance, they are not the only measure of your potential. Be confident in what you know, and stay aware of what you still need to learn. The process of learning never truly ends. There have even been times when I’ve learned something new during an exam!
Remember, a lack of confidence can cloud your mind and hinder your ability to recall what you already know. Trust yourself, embrace the process, and approach every test—whether academic or in life—as an opportunity to grow.
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The Last Problem I Refuse to Solve
I have just one problem left. But, in an act of profound self-preservation, I’m refusing to solve it.
It’s not laziness, despite appearances. Nor is it procrastination, though I admit to a strong professional interest in that discipline. It’s more of a quiet, existential calculation — the kind of decision one makes when the alternative feels far too neat. Because deep down, I suspect that solving this last problem might leave me with nothing left to live for.
You see, the problem I continue to postpone — the one that has resisted every attempt at resolution — is eradicating my stupidity.
It sounds noble, doesn’t it? A clean and final victory over foolishness. But imagine, just for a moment, what life would look like without it. No more saying the wrong thing at the wrong time. No more confidently misunderstanding simple instructions. No more replaying conversations at midnight with the growing realisation that I was, once again, the idiot in the room.
And then what? Perfection? Please. That sounds ghastly.
Stupidity, I’ve come to realise, gives my life a kind of narrative structure. It’s the recurring character that keeps returning for another season, despite poor reviews and promises of cancellation. Without it, I’d have no one left to blame, no comic relief between the tragedies, no reason to keep evolving my repertoire of apologies.
It’s also alarmingly useful. Stupidity provides me with humility — the sort that isn’t rehearsed for job interviews. It keeps me human in a world increasingly allergic to error. It makes each small success feel slightly miraculous, like watching a pigeon solve a Rubik’s Cube.
So yes, I could fix it. I could wake up tomorrow, gaze into the mirror of self-awareness, and banish stupidity forever. But then what? A life of smooth competence? Endless accuracy? Conversations without foot-in-mouth acrobatics?
No, thank you. I’ll keep my stupidity. It’s the one imperfection I’ve truly mastered.
After all, without it, I might just run out of problems — and what a disaster that would be.
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