Watch Me Complete my syllabus in 10 days

Added: 2026-05-11

[00:11:47]Okay. So, hello Si. Uh, if you want I don't know which subjects USM is. Can you please DM me in >> So, hello Si.

[00:11:57]Uh, if you want I don't know which subject USM.

[00:12:00]>> Sorry. Uh, can you please DM me in Insta? I'll try to send you what you want that subject PDF.

[00:12:08]And also so this live I'm working on my search algorithms. I have a question bank for this subject. So I'm going to practice this question bank as I already have enough basic knowledge about this subject from mid exams. I have prepared really well for mid exams.

[00:12:25]So I'm just going to go with the PDF of the question bank. So I'm going to write all the question bank.

[00:12:39]I'll revise two to three times I think already.

[00:12:47]So E section already have 75 questions including all two marks, five marks, seven marks, eight marks, 10 marks questions.

[00:13:18]com.

[00:13:21]So, we'll keep each other accountable. So first 10 minutes or any questions related to studies or academics you can ask me first 10 minutes 65 we'll do this Q&A session after that to 40 minutes we'll log in again we'll have a 10 minute Q&A session and again we'll have login session. So if you have any questions right now, please do ask me in the comments or live chat.

[00:14:16]So you can ask me. I think if you don't have any questions or doubts, we'll just start our lock in session.

[00:14:33]Yeah. Then we'll start our lockin session. We'll study for 40 minutes, right? Without any distractions or any questions. After that, we'll have a Q&A session.

[00:19:28]It actually depends on the prompt. If you really want to prompt how I ask my questions for every subject.

[00:19:45]DM me in Instagram. I'll send you the prompt for CHP or Germany or any other to satisfy specific search criteria specific search criteria. So changing the nons by even one digit.

[00:35:04]Changing the nons by even one digit completely changes the resulting hash completely changes the resulting hash.

[00:35:25]So let's just describe local maxima in hill climbing.

[00:35:34]Describe local maxima.

[00:35:40]Inhale climbing.

[00:35:50]A state in hill climbing search.

[00:36:01]That is a state in hill climbing search.

[00:36:03]that is better than all its ailments that is better than all its immediate neighbors but it's not the best possible state global maximum Global maximum at local maximum.

[00:36:53]Current state is greater than all neighbors.

[00:37:00]But current state is less than global vaccine.

[00:37:34]is better than all the states of it first and it's better than all created labor.

[00:38:19]What is uniform cost search.

[00:38:25]What is uniform cost search?

[00:38:30]UCS and uninformed search algorithm that expands nodes and uninformed search algorithm that expands nodes in order of cumulative path cost from the root. So un an inform search algorithm is an algorithm that expands nodes in order of the cumulative pass from the root cumulative path cost from the root.

[00:39:29]Gu guaranteed to find the cheapest guaranteed to find the cheapest path in a weighted graph.

[00:39:47]Data structure uses a priority cube.

[00:39:57]So searchulum solution I mean solution summarize is the means and analysis process.

[00:40:28]Means analysis process.

[00:40:38]A problem solving strategy that aims to reduce the difference between the current state and the goal state by identifying sub goals. Means and analysis is a problem solving strategy that aims to reduce the difference between the current state and the goal state by identifying sub goals.

[00:40:57]Compass current and goal states to find discrepancies.

[00:41:02]Selects actions operators specifically designed to eliminate those differences.

[00:41:07]If an operator cannot be applied, it creates a sub problem to make the operator applicable.

[00:41:26]A problem solving strategy that aims to reduce the difference between a problem solving strategy that aims to reduce the difference between the current state and the goal. state.

[00:41:47]Difference between the current state and the goal state by identifying sub goals focuses on What to do to get closer to the goal difference compass current and go state difference detection compass as current and goal states to find discrepancies.

[00:42:58]operators.

[00:43:01]Selects actions.

[00:43:07]Operators specifically designed Specifically designed to eliminate those differences.

[00:43:21]to eliminate those differences.

[00:43:29]Summarize the concept of pruning in a search tree.

[00:43:35]Summarize the concept of pruning in a surgery.

[00:43:52]A technique used in search trees especially game trees like alpha beta pruning to cut off branches that are guaranteed not to lead to an optimal solution. So a technique used in search trees especially alpha beta pruning trees uh using this one we can cut off the branches that no longer lead to the optimal or the goal solution.

[00:44:17]A technique used in search trees especially game trees like alpha beta pruning.

[00:44:45]I'm actually studying search algorithm subject for my semester exams. So if you also want to study anything it can be skills or your sim sub subjects or anything at all you can drop it in the comments and start reading it with me.

[00:44:59]Start studying it with me. As long as you study you are supposed to study with me. Yeah.

[00:45:15]Alpha beta pruning to cut off branches that are guaranteed not to lead to an optimal solution.

[00:45:40]So it is efficient.

[00:45:46]Greatly reduces the number of nodes evaluated.

[00:45:51]Greatly reduces the number of nodes evaluated.

[00:46:01]It does not affect the final result but speeds up the search significantly.

[00:46:10]does not affect the final result but speeds up the search significantly.

[00:46:35]It is commonly used in minmax algorithm in AI games like chess and Tik Tok.

[00:46:47]Minmax algorithm in AI games like chess or Tik Tok.

[00:47:07]Define admissible huristic. Admissible means it does not overestimate.

[00:47:15]So what is admissible huristic? A heristic function is admissible if it never overestimates the actual cost to reach the goal. It is optimistic, meaning it thinks the goal is closer than or exactly as far as it really is.

[00:47:36]A huristic function is admissible if it never overestimates the actual cost.

[00:47:55]the actual cost to reach the goal.

[00:48:06]It is optimistic.

[00:48:10]Meaning it thinks the goal is closer than it thinks.

[00:48:20]The goal is closer than or exactly as far as it really is.

[00:48:34]It is optimistic.

[00:48:39]It always provides a lower bound on the cost.

[00:48:44]It always provides hi on the past condition.

[00:49:09]essential for the A star search algorithm to be optimal.

[00:49:26]Example, straight line distance between two points.

[00:49:36]Straight line distance between two points.

[00:49:48]H of n is less than what is random search in AI?

[00:50:06]What is random search AI?

[00:50:12]A simple search method.

[00:50:18]A simple search method where the algorithm selects the next move or state. selects the next node or state randomly from the available options randomly from the available options rather than using a systematic or guided approach. It randomly selects the next move based on the available options rather than using a systematic or guided approach.

[00:51:00]rather than using a systematic or guided approach.

[00:51:12]It is uninformed.

[00:51:16]It has no memory or strategy.

[00:51:20]It has no memory or strategy.

[00:51:30]Its drawback is very inefficient and not guaranteed to find a solution quickly.

[00:51:38]It is very inefficient and not guaranteed to find a solution quickly.

[00:51:55]itself.

[00:51:59]How is web spidering modeled as a search problem?

[00:52:06]How is web spidering modeled as a search problem?

[00:52:28]Web spiring is modeled as a graph traversal problem where the web pages are nodes and the hyperlinks are the edges connecting them.

[00:52:41]Spider is modeled as a graph travel problem where web pages are not and hyperlinks.

[00:53:12]are the edges connecting them. So web striving is modeled as a graph travel cell problem where web pages are nodes and hyperlinks are the edges connecting them.

[00:53:29]Key points.

[00:53:33]Initial state.

[00:53:37]The seed URL.

[00:53:41]Successor function.

[00:53:52]Extracting all links from the current page.

[00:54:02]strategy usually uses BFS to cover variety or DFS to go deep into a site.

[00:54:58]A heristic used in grid.

[00:55:03]A heristic used in grid based searches like the eight puzzle where movement is restricted to horizontal and movement is restricted to horizontal and vertical steps only.

[00:55:40]No diagonals.

[00:55:47]Calculation.

[00:55:49]Sum of the absolute differences of their coordinators.

[00:55:55]Some of the absolute differences of the coordinates context also called CT block distance for D is equal = x1 - x2 + y1 - y2 What is the X11 algorithm?

[00:58:24]What is the X11 algorithm in the context of search and hashing?

[00:58:37]In the context of search and hashing, X11 is a chain hashing algorithm.

[00:58:51]is a chain hashing algorithm that uses a sequence of 11 different scientific hashing functions to secure a network.

[00:59:19]So in the context of search and hashing, X11 is a chained chain hashing algorithm that uses a sequence of 11 different scientific hashing functions to secure a network. The purpose is created to make the search for a valid hash more complex and resistant to spec specialized hardware. The output of one hash function becomes the input for the next.

[00:59:43]uses 11 different algorithms like Blake, BMW, Bro, etc. in a specific order.

[00:59:51]Okay, so I think uh let's wrap up the first session. Uh we'll go to the Q&A session right now and then after that we'll have another live session of login. So if you have any doubts or if you want to know anything you can just comment it in the live chat and we'll discuss about it.

[01:00:42]Okay. So, let me give you a tip for saying PTS.

[01:00:57]So, uh many people have asked me Instagram.

[01:01:04]First of all, you're completely prepared.

[01:01:22]You can go on the stage and say it very clearly.

[01:01:28]You can do one thing.

[01:01:33]Take your own space and then breathe in and then breathe out. First feel comfortable on the stage like able you can start reading the slides and by reading the slides I don't mean just read just that will not be worth it you need to understand what is there you need to say what you understood or you can prepare script from chat or Germany or anything it will take around just 10 15 minutes just 10 15 It will be very you can use AI for that also.

[01:02:34]Main thing stage you need to have your own script.

[01:02:52]Third thing, you need to have proper knowledge about the topic.

[01:03:00]You should be able to answer the questions.

[01:03:04]Yep.

[01:03:08]So, if you have any more questions