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Abhay Kumar

@maths_seekho

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Making Maths Simple ⚡
IIT-JEE & GATE Qualified 🎓
NITian | [email protected]

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What is the unit of π?
#maths #mathematics #olympiad #iitjee #neet taken in Bangalore, India by @maths_seekho

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3k

10 months ago

Post your solution.
Open challenge.
#maths #mathematics #viral #olympiad #jeemains taken in Bangalore, India by @maths_seekho

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9 months ago

What is the LCM of π and π² ? #olympiad #maths #mathematics #jeeadvanced #iitjee taken in Bangalore, India by @maths_seekho

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3k

10 months ago

30% OFF ya 20% + extra 12.5%? Alag offer, same ₹14,000! 🤯

Maths batata hai kitna pay karoge. AI tumhare clicks se seekh sakta hai kaunsa ad tumhe dikhaye. 🛒🤖

Maximum saving ka mera hack? App uninstall. 😂

Calculation se pehle tum kaunsa offer choose karte? 👇

#ShoppingMaths #AI #MachineLearning #SmartShopping #mathsinreallife taken in Bangalore, India by @maths_seekho

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3 hours ago

Don’t use AI just because it sounds smart.
If simple rules can solve the problem, use code.
If context, scale, or ambiguity makes rules break down, that’s where ML/AI starts adding value.
Example: detecting known names → simple code.
Detecting any personal name in thousands of requirements → NER/AI.
#AI #MachineLearning #SoftwareEngineering #RequirementsEngineering #nlp taken in Bangalore, India by @maths_seekho

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4 days ago

Don’t use AI just because you can. Use it because the problem actually needs it.
Simple rules + clear boundaries? Regular code may be enough.
But when language gets contextual, meanings overlap, and thousands of requirements need classification, handcrafted rules start breaking down. That’s where ML/AI becomes useful.
Simple boundary → Simple code
Complex boundary → Machine Learning
Context-heavy language → AI
#AI #MachineLearning #SoftwareEngineering #RequirementsEngineering #artificialintelligence taken in Bangalore, India by @maths_seekho

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6 days ago

Bayes’ Theorem isn’t just a school probability formula — it’s a way to update belief when new evidence arrives.

In an AEB system, a camera may initially detect something ahead with moderate confidence. Radar, object tracking, motion and road context add more evidence. As the evidence becomes stronger, the system’s belief that the object is a pedestrian — and that a collision risk exists — gets updated.

That’s the basic idea behind Bayesian thinking:
Prior belief + New evidence → Updated belief
ML helps detect and classify.
Probabilistic reasoning helps handle uncertainty.

AI uses that information to make a safer decision.
From Class 12 probability to real-world automotive AI. 🚗🧠
#artificialintelligence #machinelearning #maths #probability #automotive taken in Bangalore, India by @maths_seekho

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12 days ago

Should I do this Collab ??
#collab #instagram #money #influencer #india taken in Bangalore, India by @maths_seekho

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16 days ago

Machine Learning M.Tech 1st Sem
#mtech #machinelearning #artificialintelligence #aiml #viral taken in Bangalore, India by @maths_seekho

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a month ago

Open book Exam scam.
#exam #openbook #collegelife #science taken in Bangalore, India by @maths_seekho

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a month ago

AI & ML = Maths
#artificialintelligence #machinelearning #mathematics #collegelife #iit taken in Bangalore, India by @maths_seekho

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2 months ago

What is the probability of randomly selecting exactly 0.5 from all real numbers between 0 and 1? #maths #mathematics #olympiad #viral #cbse taken in Bangalore, India by @maths_seekho

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5 months ago