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Engineers Ka Adda
India
Приєднався 4 вер 2017
Welcome to ENGINEERS KA ADDA , your hub for in-depth theory lessons in Computer Science Engineering and Electrical Engineering!
Our goal is to simplify complex theories and make them accessible to learners at all levels for absolutely FREE along with FREE NOTES. Whether you're a student aiming to grasp fundamental concepts or a professional seeking to deepen your understanding, you'll find valuable insights and explanations here.
Subscribe to ENGINEERS KA ADDA for clear, concise theory lessons that will enhance your knowledge and expertise in CSE and Electrical Engineering!
Our goal is to simplify complex theories and make them accessible to learners at all levels for absolutely FREE along with FREE NOTES. Whether you're a student aiming to grasp fundamental concepts or a professional seeking to deepen your understanding, you'll find valuable insights and explanations here.
Subscribe to ENGINEERS KA ADDA for clear, concise theory lessons that will enhance your knowledge and expertise in CSE and Electrical Engineering!
Web Technology | What is HTML | HTML Basics | HTML Tags & HTML Sections
Welcome to the Web Technology Playlist! 🎉
In this video, we’re diving into the Basics of Web Technology. 🚀
#html #webtechnology #html5
📌 Topics Covered:
Introduction to HTML
Understanding HTML Tags
Key Sections in HTML
Whether you’re a beginner or brushing up on your web development skills, this video is a great starting point.
💡 Stay Tuned: This is just the beginning! We’ll explore CSS, JavaScript, and much more in this playlist.
📢 Don’t forget to Like, Subscribe, and Share to stay updated with new videos.
👉 Follow Along:
🔗 Playlist Link: [Add Playlist Link]
Let’s build the web together! 🌐
In this video, we’re diving into the Basics of Web Technology. 🚀
#html #webtechnology #html5
📌 Topics Covered:
Introduction to HTML
Understanding HTML Tags
Key Sections in HTML
Whether you’re a beginner or brushing up on your web development skills, this video is a great starting point.
💡 Stay Tuned: This is just the beginning! We’ll explore CSS, JavaScript, and much more in this playlist.
📢 Don’t forget to Like, Subscribe, and Share to stay updated with new videos.
👉 Follow Along:
🔗 Playlist Link: [Add Playlist Link]
Let’s build the web together! 🌐
Переглядів: 44
Відео
Dempster Shafer Theory in artificial intelligence | Artificial intelligence lectures
Переглядів 83621 день тому
Welcome to our channel! 🚀 In this video, we dive into the fascinating world of Dempster-Shafer Theory, an essential concept in Artificial Intelligence and decision-making under uncertainty. 🧠✨ Notes- drive.google.com/drive/folders/1kWvxcgmGuLmJ-aapkCNiDgVQVRp0XkLv What you'll learn in this video: ✅ Introduction to Dempster-Shafer Theory: What it is and why it matters. ✅ Basic Concepts: Belief f...
Monotonic & non-monotonic reasoning in AI | Default reasoning & Closed world assumption in AI
Переглядів 128Місяць тому
In this video, we’ll dive into key reasoning concepts in Artificial Intelligence (AI), including Monotonic and Non-Monotonic Reasoning. You’ll learn how monotonic reasoning assumes knowledge remains consistent, while non-monotonic reasoning allows for flexibility when new information is introduced. We’ll also explore Default Reasoning, which makes assumptions in the absence of complete data, an...
Tower of hanoi in hindi in Artificial Intelligence | Artificial intelligence lectures
Переглядів 39Місяць тому
#towerofhanoi #towerofhanoiprobleminai In this video, we'll dive into the challenges and problems facing the field of Artificial Intelligence (AI). From ethical concerns like bias and privacy issues to technical challenges such as data quality, interpretability, and the need for vast computational resources, we'll explore the complexities that researchers and developers encounter when working w...
Syntax and Semantics in First order logic | Artificial intelligence lectures for students
Переглядів 127Місяць тому
In this video, we’ll break down the syntax and semantics of First Order Predicate Logic (FOPL), a foundational concept in Artificial Intelligence (AI) and formal logic. You’ll learn about the structure (syntax) of FOPL, including predicates, variables, constants, quantifiers, and connectives. We’ll also cover the semantics, explaining how FOPL interprets statements to assign truth values and ma...
Game playing in AI and Adverserial search algorithm | Aritificial intelligence lectures for students
Переглядів 39Місяць тому
In this video, we’ll explore game-playing strategies and adversarial search techniques in Artificial Intelligence (AI). You’ll learn how AI competes in two-player games using adversarial search methods like Minimax and Alpha-Beta pruning to make optimal moves against an opponent. We’ll break down how these algorithms work in games like Chess and Tic-Tac-Toe, where AI evaluates possible moves, a...
Constraints satisfaction problem in Artificial Intelligence with real example | Map coloring problem
Переглядів 61Місяць тому
In this video, we dive into the fundamentals of Constraint Satisfaction Problems (CSP) and their crucial role in Artificial Intelligence. CSPs are powerful tools used to solve complex problems by defining constraints and finding solutions that satisfy them. From scheduling tasks to puzzle-solving and resource allocation, CSPs are everywhere! Notes :- drive.google.com/drive/folders/1YpoU4SucldOb...
Genetic algorithm in artificial intelligence | artificial intelligence playlist |
Переглядів 93Місяць тому
In this video, we’ll dive into the Genetic Algorithm (GA), an optimization technique inspired by natural evolution, used in Artificial Intelligence (AI) for solving complex problems. You’ll learn how GA works by simulating biological processes like selection, crossover, and mutation to evolve a population of solutions over generations. We’ll break down each step and show how this algorithm is a...
Hill climbing algorithm in Artificial Intelligence | artificial intelligence playlist
Переглядів 92Місяць тому
Notes:- drive.google.com/drive/folders/1Vw0AAvrGy4ME_m3fv08jmdn8cw_j6a0y In this video, we’ll explore the Hill Climbing algorithm, a popular optimization technique in Artificial Intelligence (AI) used for solving complex problems. You’ll learn how this algorithm works by iteratively moving towards a better solution, and how it evaluates the "fitness" of each step to climb toward an optimal goal...
A* Search Algorithm in artificial intelligence | A star search algorithm example | search algorithm
Переглядів 812 місяці тому
A* (A-Star) Search Algorithm Explained! | Artificial Intelligence 🤖 Notes :- drive.google.com/drive/folders/1WGR1-NUcNc6jCcrkQri-KQwtkVao6mqN In this video, we’ll break down one of the most powerful and popular algorithms in Artificial Intelligence - the A (A-Star) Search Algorithm*. This algorithm is widely used in pathfinding and graph traversal applications like gaming, robotics, and network...
More about HTML and CSS | Master CSS Styling: Borders, Backgrounds, Flexbox & More!
Переглядів 892 місяці тому
🎨 Master CSS Styling: Borders, Backgrounds, Flexbox & More! 💻 In this video, we’ll explore essential CSS styling techniques to bring your web pages to life! Perfect for beginners and intermediate coders, this tutorial will cover: 🔹 Borders - Learn how to add and customize borders to elements. 🔹 Background Color - Apply vibrant or subtle backgrounds to enhance your page design. 🔹 Flexbox - Maste...
Web development for beginners | HTML , CSS & JAVASCRIPT | Introduction to html and CSS
Переглядів 742 місяці тому
#webdevelopmentforbeginners #htmltutorial #csstutorial 🎯 Welcome to the Basics of HTML, CSS, and JavaScript! 🚀 In this video, we’ll be diving into the foundational building blocks of web development! Whether you're a complete beginner or looking to refresh your skills, this tutorial will guide you through the essentials: 🔹 HTML - Learn how to structure web pages using tags, elements, and attrib...
Best first search & Bidirectional search | Heuristic search with example in AI
Переглядів 472 місяці тому
Notes - drive.google.com/drive/folders/1JArSErCl2om9GqqFU8JtKSiV7-joMiTc #heuristics #bestfirstsearch #bidirectional In this video, we’ll explore two powerful search techniques in Artificial Intelligence (AI): Bidirectional Search and Best-First Search. You’ll learn how bidirectional search works by simultaneously searching from both the start and goal, cutting down the search time significantl...
Solving problem by searching | Uninformed search | Informed search & heuristic search | Bfs dfs
Переглядів 442 місяці тому
#uninformedsearch #informedsearch #heuristic In this video, we’ll explore how Artificial Intelligence (AI) solves problems using search algorithms. You’ll learn about different types of searches, including uninformed search methods like breadth-first and depth-first, as well as informed search techniques like A* and greedy search. We’ll discuss how AI explores the problem space to find the most...
Mini-Max algorithm | Alpha beta pruning | Mini-Max algorithm in artificial intelligence in game play
Переглядів 912 місяці тому
Notes link :- drive.google.com/drive/folders/1IIdH_Xhz-A5gHwERjzkYG9FxP92F7tg2 #minimax #minmax #tictactoe #alphabeta #alphabetapruning In this video, we’ll explore two fundamental AI techniques used in game theory: the Minimax algorithm and Alpha-Beta Pruning. We’ll start by explaining how the Minimax algorithm helps AI make optimal decisions in two-player games like chess and Tic-Tac-Toe by m...
Tic Tac Toe in Artificial Intelligence | tic tac toe game using artificial intelligence | TicTac Toe
Переглядів 1043 місяці тому
Tic Tac Toe in Artificial Intelligence | tic tac toe game using artificial intelligence | TicTac Toe
Problem characteristics in artificial intelligence | stochastic problem | well defined problem
Переглядів 2403 місяці тому
Problem characteristics in artificial intelligence | stochastic problem | well defined problem
State space search in artificial intelligence | state space search tree | Artificial Intelligence
Переглядів 553 місяці тому
State space search in artificial intelligence | state space search tree | Artificial Intelligence
Problem space and search space in artificial intelligence with example | Lecture 5
Переглядів 623 місяці тому
Problem space and search space in artificial intelligence with example | Lecture 5
problem solving in artificial intelligence | Steps to TRAIN AI System's
Переглядів 493 місяці тому
problem solving in artificial intelligence | Steps to TRAIN AI System's
Techniques in Artificial intelligence | Types of techniques in AI | Machine learning
Переглядів 563 місяці тому
Techniques in Artificial intelligence | Types of techniques in AI | Machine learning
PROBLEMS in ARTIFICIAL INTELLIGENCE | Will AI replace Jobs in future | Issues in AI
Переглядів 483 місяці тому
PROBLEMS in ARTIFICIAL INTELLIGENCE | Will AI replace Jobs in future | Issues in AI
Introduction to ARTIFICIAL INTELLIGENCE(AI) | Introduction to AI | Uses, Techniques, Types of AI |
Переглядів 1153 місяці тому
Introduction to ARTIFICIAL INTELLIGENCE(AI) | Introduction to AI | Uses, Techniques, Types of AI |
Bit plane coding | Question on bit plane coding | Bit plane coding example |digital image processing
Переглядів 2004 місяці тому
Bit plane coding | Question on bit plane coding | Bit plane coding example |digital image processing
lossy predective coding | Question on lossy predective coding | digital image processing
Переглядів 3314 місяці тому
lossy predective coding | Question on lossy predective coding | digital image processing
lossless predective coding | digital image processing | Image compression digital image processing
Переглядів 1634 місяці тому
lossless predective coding | digital image processing | Image compression digital image processing
Variable Length Coding | Image Compression in Digital Image Processing
Переглядів 5094 місяці тому
Variable Length Coding | Image Compression in Digital Image Processing
Multi resolution expansion| Multi resolution analysis in digital image processing| image compression
Переглядів 2834 місяці тому
Multi resolution expansion| Multi resolution analysis in digital image processing| image compression
Wavelets and Background in Digital Image Processing | Image compression | Digital Image Processing
Переглядів 1604 місяці тому
Wavelets and Background in Digital Image Processing | Image compression | Digital Image Processing
Most commonly asked questions in DIGITAL IMAGE PROCESSING | Important topics in image processing
Переглядів 2224 місяці тому
Most commonly asked questions in DIGITAL IMAGE PROCESSING | Important topics in image processing
Nice explanation 😌
Thanks a lot😄
@@engineerskaadda78 I don't know Hindi but I have got clear idea on concept 😅
@@k.tejareddy0272 that's something great to hear for me, u can check notes for complete information in english
0100
Thank you sir ❤
Welcome dear ❤️
Starting was osm sir 👍
Thank you so much
Explain the state-of-the-art bidirectional heuristic search BAE*.
@@Dr.SamirKumarSadhukhan-jw1wk didnt got yoir point sir , is this a new topic or something I missed in this topic?
BAE* is the new bidirectional heuristic search. See the paper "Bidirectional heuristic search using error estimate" And other referenced papers.
@@Dr.SamirKumarSadhukhan-jw1wk ok thnkx for the information ❤️
there are more easy videos explaining eigen values and vectors but in general this is fine. although you dont have to mug up the equation it can easily be solved until you gasp the concept
Yes sir , my goal is to explain the concept of SVD , not how to solve small equations. Thnkx for your valuable comment❤️
Sir, while solving DST problem while finding m5 (i already have m1,m2,m3,m4) i got 2 plausibility cases , what should we do in this case? earlier if there was i plausibility case we used to calc plausibility and divide everything with it but in this case i got 2 plausibility cases please help
Ok so here i will explain you few steps u can try and also a example to be more specific , hope u understand- Step 1: Understand the Two Plausibility Cases Each plausibility case corresponds to a different subset or hypothesis in the frame of discernment. For each case, calculate the plausibility value based on the combination of the masses 𝑚1, 𝑚2, 𝑚3, 𝑚4 Step 2: Determine if the Cases Overlap If the two plausibility cases overlap (i.e., they pertain to subsets that are not mutually exclusive), combine the plausibility values by adding them. This is because their joint plausibility contributes to the overall belief in the union of these subsets. If the cases are disjoint (i.e., they pertain to subsets that have no common elements), handle them as separate hypotheses. You would then assign their masses separately and normalize afterward. Step 3: Normalize the Masses Add up all the resulting masses, including those from the two plausibility cases. Normalize by dividing each mass by the sum of the plausibilities to ensure the total mass equals 1. Example: Let’s say: 𝑚1(𝐴)=0.3 𝑚2(𝐴)=0.4 𝑚3(𝐵)=0.2 𝑚4(𝐶)=0.1 𝑚5 has two plausibility cases: Case 1: Plausibility for 𝐴∪𝐵= 0.6 Case 2: Plausibility for 𝐶 = 0.4 Steps: 1.Combine A∪B and 𝐶 if possible, or treat them as separate. 2.Calculate the total plausibility sum: Total Plausibility= 0.6+0.4=1.0 3.Normalize: 𝑚5(𝐴∪𝐵)=0.6/1.0=0.6 𝑚5(C)=0.4/1.0=0.4
@engineerskaadda78 Thankyou for the quick reply, it's very helpful 👍🏻
@@kratosss9981 its my pleasure dear❤️
Very nice explaination👌👌👌
Thnkx a lot❤️
👍
😻
Sir X1 [0 1] kese liya
Initially X1=[a b] ha , then A or B ka value find kar k , humlog bas value put kr diye waha pai
Nice explanation
Thankss❤️
Nicee ❤
Thanks 🔥
good explanation 👌
Thank you 😄
👍
Well explained 👏🏻
Thanks a lot❤️
Great 👍 Started your playlist... hoping for soon complition of syllabus 😊
❤️❤️
Really helpful, thnku for the video sir , such a content is not available in all over youtube ❤
Glad it helped u sir❤️
sir aapke mosi kane se 0a+3b=3b => -a+0b=0 A tranpose A aaya h
👍
THE TRICKS YOU USED FOR COMPUTING EIGEN VECTOR AND VALUES WILL NOT WORK WITH HARD PROBLEMS YOU DID NOT COMPUTE CHARACTERISTIC POLYNOMIAL NOR CHARACTERISTIC EQUATION AND DID A SHORTCUT TO FIND EIGEN VECTOR WITHOUT THE EQUATION IF I SOLVED THE QUESTION WITH THIS WAY IN EXAM I WILL GET 0 VERY. TIME WASTED
Yes but for btech level , u won't get harder questions than this. That's y , only need to learn how much is required
😂😂 too good
👍🏻👍🏻
❤️❤️
Good 👍
Thnkx❣️
In Ideal low pass all values are greater than to D0. So all values will be zero except 1
Yess
nhi app basic bhi btaiye nhi tu pta hi hai kya hoga
Ok
Thank you so much 🙏🙏
Wlcm❤️
Best explanation 😀 thanku sir 🥰
Thnku for the compliment ❣️ kindly share❤️
👍🏻👍🏻👍🏻
0 +3b = 3b iska ans -a + 0b = 0 yeh wala part chi samjha
0+3b = 3b ok thats correct; but then see eqn 1 , waha likha ha -a+0b =0 , means -a = 0. Ok ! Then 0 +3b =3b (from matrix) so replace 0 with -a and 3b , 3b cancel out , so it becomes again -a + 0b = 0. Ok understood?
please take a tougher problem on this topic
Sure will surely make
Nice explanation. 😊. But Weiner fillter ka notes nhi upload hai discription me .. . Dubra se order statistic ka hi link hh
Ok thnkx for pointing out. Check after few hours , i will update it
Nice❤
Thnkxx❤️🙏
Bhaiya 7th sem data science, ML, iot, Ai se koi project batao
For minor project u can try basic projects like "text to speech conversion system", "speech to speech conversion system", "fraud detection", "recommendation system". And for little good projects u can try for "stock price predection system", "email spam filtering system", "basic chatbots", "creditcard fraud detection system".
now my doubt has been cleared regarding evaluation ...thank you so much sir...🎉🎈
Thats really nice to hear 😊 happy to help u
superb explanation sir..
Thnku sir❤️
Nicely explained thanks for the video sir❤
Glad u liked it❤️
eigon vectors galat hai jab u calculate kar rhe hai
Aisa to nhi ho sakta sir. Maybe kuch glti huyi ho aapse ya mujhse. But follow the process , process is important, process samjhna ha
@@engineerskaadda7820.48 jis equation se lembda=2 k liye eigon vector nikla h vo equation m vo vector put krke dekio satisfy nhi ho rha h
Nice session sir ❤
Thnku❤️
simply follow the rule: Bhai ne bola karne ka to karne ka isiliye topic hi chod diya
😂😂good
Bhaiya Jut ka syllabus pe base hai na
Haa. Apne sare batchmastes k sath share kr dena❤️
@@engineerskaadda78 ofcourse bhai... Cryptography and data mining and warehouse pe banao Bhaiya
@@shubhamkumar9895 sab ek sath to nhi bana sakte. Dekhte ha jitna cover sakte ha
Great explanation 👏
Thnku
❤
❤️
great explanation sir
Thnkx a lot dear❤️
Time waste 😑
Sir.. aapp bich bich me negetivity me kyu bolte ho 🙂 bhai smjaoo ... Teaching skill chnge krooo
Ok thnkx for suggestion, will improve !! Check other videos also of the playlist. This is a numerical , nothing much here to make u understand ,u should have strong mathematics dear , then it will be crystal clear.
👏
❤️