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LearnAlgorithm 💻

It's a new way of learning Algorithms. The aim of this project is to provide interactive explanations of different AI Algorithms.

Is this project solving any problem ❓

Before I discuss about the project let me tell you about the problems that this project will solve. Nowadays students are less interested to read books or attend any lectures because somehow they find it boring or intimidating.

Nowadays, students are more interested to see some nice interactive explanations on the web. This project aims to create some good interactive explanations of AI algorithms such as Best First Search, Natural Language Processing, Search Algorithms, Regression models etc. basically I want to design some sort of games to explain how different algorithms works.

Let's see an Example: 🔎

Greedy Best First Algorithm - Interactive Explanation Demo

For some moments Stop thinking 🤔 about any algorithms and look at this diagram: 👇

1st

Suppose, you’re travelling from your office to your home and you want to reach as soon as possible, then which path will you choose? Think for a while. 🤔

Ok, now let's look at the next diagram: 👇

2nd

If I’m not wrong, you might have thought about this path, which seems the shortest among all, right? If it is right then you’ve just tried to be greedy. 💰

In this way, we as a human, decide which case/path is best for us. Now let's think from an computer's perspective. I think you all have played Counter Strike! **Have you ever wondered how an enemy agent finds the location of the player in the Game World? **

This is where Algorithms comes into play. In games, Best-first search may be used as a path-finding algorithm for game characters.

For a better understanding of Greedy Best First Search Algorithm, I've created a basic interactive game which you might want to play to have a better understanding. Head over to this link and scroll down to find the game.

Planning for future:

As of now, I've only created the visualization for Greedy Best Search Algorithm. So I'm planning to create more visualization to certain search algorithms like: Dijkstra's Algorithm, A* Algorithm, Depth First Search, Breadth First Search and some Machine Algorithms like Linear Regression etc.

About

A new way of learning Algorithms.

souravinsights.github.io/LearnAlgorithm/

Topics

alogrithmshactoberfestinteractive-visualizationsvisualization

Resources

Readme
MIT license
Activity

Stars

1 star

Watchers

0 watching

Forks

3 forks
Report repository

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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LearnAlgorithm 💻
It's a new way of learning Algorithms. The aim of this project is to provide interactive explanations of different AI Algorithms.
Is this project solving any problem ❓
Before I discuss about the project let me tell you about the problems that this project
will solve. Nowadays students are less interested to read books or attend any lectures
because somehow they find it boring or intimidating.
Nowadays, students are more interested to see some nice interactive explanations on the web.
This project aims to create some good interactive explanations of AI algorithms such as
Best First Search, Natural Language Processing, Search Algorithms, Regression models
etc. basically I want to design some sort of games to explain how different algorithms
works.
Let's see an Example: 🔎
Greedy Best First Algorithm - Interactive Explanation Demo
For some moments Stop thinking 🤔 about any algorithms and look at this diagram: 👇
1st
Suppose, you’re travelling from your office to your home and you want to reach as soon as possible, then which path will
you choose? Think for a while. 🤔
Ok, now let's look at the next diagram: 👇
2nd
If I’m not wrong, you might have thought about this path, which seems the shortest among all, right?
If it is right then you’ve just tried to be greedy. 💰
In this way, we as a human, decide which case/path is best for us. Now let's think from an computer's perspective.
I think you all have played Counter Strike! **Have you ever wondered how an enemy agent finds the location of the player in the
Game World? **
This is where Algorithms comes into play. In games, Best-first search may be used as a path-finding algorithm for game characters.
For a better understanding of Greedy Best First Search Algorithm, I've created a basic interactive game which you might want to play to have
a better understanding. Head over to this link and scroll down to find the game.
Planning for future:
As of now, I've only created the visualization for Greedy Best Search Algorithm. So I'm planning to create more visualization to certain
search algorithms like: Dijkstra's Algorithm, A* Algorithm, Depth First Search, Breadth First Search and some Machine Algorithms like
Linear Regression etc.
About
A new way of learning Algorithms.
souravinsights.github.io/LearnAlgorithm/
Topics
alogrithmshactoberfestinteractive-visualizationsvisualization
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
0 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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LearnAlgorithm 💻
It's a new way of learning Algorithms. The aim of this project is to provide interactive explanations of different AI Algorithms.
Is this project solving any problem ❓
Before I discuss about the project let me tell you about the problems that this project
will solve. Nowadays students are less interested to read books or attend any lectures
because somehow they find it boring or intimidating.
Nowadays, students are more interested to see some nice interactive explanations on the web.
This project aims to create some good interactive explanations of AI algorithms such as
Best First Search, Natural Language Processing, Search Algorithms, Regression models
etc. basically I want to design some sort of games to explain how different algorithms
works.
Let's see an Example: 🔎
Greedy Best First Algorithm - Interactive Explanation Demo
For some moments Stop thinking 🤔 about any algorithms and look at this diagram: 👇
1st
Suppose, you’re travelling from your office to your home and you want to reach as soon as possible, then which path will
you choose? Think for a while. 🤔
Ok, now let's look at the next diagram: 👇
2nd
If I’m not wrong, you might have thought about this path, which seems the shortest among all, right?
If it is right then you’ve just tried to be greedy. 💰
In this way, we as a human, decide which case/path is best for us. Now let's think from an computer's perspective.
I think you all have played Counter Strike! **Have you ever wondered how an enemy agent finds the location of the player in the
Game World? **
This is where Algorithms comes into play. In games, Best-first search may be used as a path-finding algorithm for game characters.
For a better understanding of Greedy Best First Search Algorithm, I've created a basic interactive game which you might want to play to have
a better understanding. Head over to this link and scroll down to find the game.
Planning for future:
As of now, I've only created the visualization for Greedy Best Search Algorithm. So I'm planning to create more visualization to certain
search algorithms like: Dijkstra's Algorithm, A* Algorithm, Depth First Search, Breadth First Search and some Machine Algorithms like
Linear Regression etc.
About
A new way of learning Algorithms.
souravinsights.github.io/LearnAlgorithm/
Topics
alogrithmshactoberfestinteractive-visualizationsvisualization
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
0 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
LearnAlgorithm 💻
It's a new way of learning Algorithms. The aim of this project is to provide interactive explanations of different AI Algorithms.
Is this project solving any problem ❓
Before I discuss about the project let me tell you about the problems that this project
will solve. Nowadays students are less interested to read books or attend any lectures
because somehow they find it boring or intimidating.
Nowadays, students are more interested to see some nice interactive explanations on the web.
This project aims to create some good interactive explanations of AI algorithms such as
Best First Search, Natural Language Processing, Search Algorithms, Regression models
etc. basically I want to design some sort of games to explain how different algorithms
works.
Let's see an Example: 🔎
Greedy Best First Algorithm - Interactive Explanation Demo
For some moments Stop thinking 🤔 about any algorithms and look at this diagram: 👇
1st
Suppose, you’re travelling from your office to your home and you want to reach as soon as possible, then which path will
you choose? Think for a while. 🤔
Ok, now let's look at the next diagram: 👇
2nd
If I’m not wrong, you might have thought about this path, which seems the shortest among all, right?
If it is right then you’ve just tried to be greedy. 💰
In this way, we as a human, decide which case/path is best for us. Now let's think from an computer's perspective.
I think you all have played Counter Strike! **Have you ever wondered how an enemy agent finds the location of the player in the
Game World? **
This is where Algorithms comes into play. In games, Best-first search may be used as a path-finding algorithm for game characters.
For a better understanding of Greedy Best First Search Algorithm, I've created a basic interactive game which you might want to play to have
a better understanding. Head over to this link and scroll down to find the game.
Planning for future:
As of now, I've only created the visualization for Greedy Best Search Algorithm. So I'm planning to create more visualization to certain
search algorithms like: Dijkstra's Algorithm, A* Algorithm, Depth First Search, Breadth First Search and some Machine Algorithms like
Linear Regression etc.
About
A new way of learning Algorithms.
souravinsights.github.io/LearnAlgorithm/
Topics
alogrithmshactoberfestinteractive-visualizationsvisualization
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
0 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
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LearnAlgorithm 💻
It's a new way of learning Algorithms. The aim of this project is to provide interactive explanations of different AI Algorithms.
Is this project solving any problem ❓
Before I discuss about the project let me tell you about the problems that this project
will solve. Nowadays students are less interested to read books or attend any lectures
because somehow they find it boring or intimidating.
Nowadays, students are more interested to see some nice interactive explanations on the web.
This project aims to create some good interactive explanations of AI algorithms such as
Best First Search, Natural Language Processing, Search Algorithms, Regression models
etc. basically I want to design some sort of games to explain how different algorithms
works.
Let's see an Example: 🔎
Greedy Best First Algorithm - Interactive Explanation Demo
For some moments Stop thinking 🤔 about any algorithms and look at this diagram: 👇
1st
Suppose, you’re travelling from your office to your home and you want to reach as soon as possible, then which path will
you choose? Think for a while. 🤔
Ok, now let's look at the next diagram: 👇
2nd
If I’m not wrong, you might have thought about this path, which seems the shortest among all, right?
If it is right then you’ve just tried to be greedy. 💰
In this way, we as a human, decide which case/path is best for us. Now let's think from an computer's perspective.
I think you all have played Counter Strike! **Have you ever wondered how an enemy agent finds the location of the player in the
Game World? **
This is where Algorithms comes into play. In games, Best-first search may be used as a path-finding algorithm for game characters.
For a better understanding of Greedy Best First Search Algorithm, I've created a basic interactive game which you might want to play to have
a better understanding. Head over to this link and scroll down to find the game.
Planning for future:
As of now, I've only created the visualization for Greedy Best Search Algorithm. So I'm planning to create more visualization to certain
search algorithms like: Dijkstra's Algorithm, A* Algorithm, Depth First Search, Breadth First Search and some Machine Algorithms like
Linear Regression etc.
About
A new way of learning Algorithms.
souravinsights.github.io/LearnAlgorithm/
Topics
alogrithmshactoberfestinteractive-visualizationsvisualization
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
0 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
LearnAlgorithm 💻
It's a new way of learning Algorithms. The aim of this project is to provide interactive explanations of different AI Algorithms.
Is this project solving any problem ❓
Before I discuss about the project let me tell you about the problems that this project
will solve. Nowadays students are less interested to read books or attend any lectures
because somehow they find it boring or intimidating.
Nowadays, students are more interested to see some nice interactive explanations on the web.
This project aims to create some good interactive explanations of AI algorithms such as
Best First Search, Natural Language Processing, Search Algorithms, Regression models
etc. basically I want to design some sort of games to explain how different algorithms
works.
Let's see an Example: 🔎
Greedy Best First Algorithm - Interactive Explanation Demo
For some moments Stop thinking 🤔 about any algorithms and look at this diagram: 👇
1st
Suppose, you’re travelling from your office to your home and you want to reach as soon as possible, then which path will
you choose? Think for a while. 🤔
Ok, now let's look at the next diagram: 👇
2nd
If I’m not wrong, you might have thought about this path, which seems the shortest among all, right?
If it is right then you’ve just tried to be greedy. 💰
In this way, we as a human, decide which case/path is best for us. Now let's think from an computer's perspective.
I think you all have played Counter Strike! **Have you ever wondered how an enemy agent finds the location of the player in the
Game World? **
This is where Algorithms comes into play. In games, Best-first search may be used as a path-finding algorithm for game characters.
For a better understanding of Greedy Best First Search Algorithm, I've created a basic interactive game which you might want to play to have
a better understanding. Head over to this link and scroll down to find the game.
Planning for future:
As of now, I've only created the visualization for Greedy Best Search Algorithm. So I'm planning to create more visualization to certain
search algorithms like: Dijkstra's Algorithm, A* Algorithm, Depth First Search, Breadth First Search and some Machine Algorithms like
Linear Regression etc.
About
A new way of learning Algorithms.
souravinsights.github.io/LearnAlgorithm/
Topics
alogrithmshactoberfestinteractive-visualizationsvisualization
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
0 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
LearnAlgorithm 💻
It's a new way of learning Algorithms. The aim of this project is to provide interactive explanations of different AI Algorithms.
Is this project solving any problem ❓
Before I discuss about the project let me tell you about the problems that this project
will solve. Nowadays students are less interested to read books or attend any lectures
because somehow they find it boring or intimidating.
Nowadays, students are more interested to see some nice interactive explanations on the web.
This project aims to create some good interactive explanations of AI algorithms such as
Best First Search, Natural Language Processing, Search Algorithms, Regression models
etc. basically I want to design some sort of games to explain how different algorithms
works.
Let's see an Example: 🔎
Greedy Best First Algorithm - Interactive Explanation Demo
For some moments Stop thinking 🤔 about any algorithms and look at this diagram: 👇
1st
Suppose, you’re travelling from your office to your home and you want to reach as soon as possible, then which path will
you choose? Think for a while. 🤔
Ok, now let's look at the next diagram: 👇
2nd
If I’m not wrong, you might have thought about this path, which seems the shortest among all, right?
If it is right then you’ve just tried to be greedy. 💰
In this way, we as a human, decide which case/path is best for us. Now let's think from an computer's perspective.
I think you all have played Counter Strike! **Have you ever wondered how an enemy agent finds the location of the player in the
Game World? **
This is where Algorithms comes into play. In games, Best-first search may be used as a path-finding algorithm for game characters.
For a better understanding of Greedy Best First Search Algorithm, I've created a basic interactive game which you might want to play to have
a better understanding. Head over to this link and scroll down to find the game.
Planning for future:
As of now, I've only created the visualization for Greedy Best Search Algorithm. So I'm planning to create more visualization to certain
search algorithms like: Dijkstra's Algorithm, A* Algorithm, Depth First Search, Breadth First Search and some Machine Algorithms like
Linear Regression etc.
About
A new way of learning Algorithms.
souravinsights.github.io/LearnAlgorithm/
Topics
alogrithmshactoberfestinteractive-visualizationsvisualization
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
0 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
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})();
})();

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LearnAlgorithm 💻
It's a new way of learning Algorithms. The aim of this project is to provide interactive explanations of different AI Algorithms.
Is this project solving any problem ❓
Before I discuss about the project let me tell you about the problems that this project
will solve. Nowadays students are less interested to read books or attend any lectures
because somehow they find it boring or intimidating.
Nowadays, students are more interested to see some nice interactive explanations on the web.
This project aims to create some good interactive explanations of AI algorithms such as
Best First Search, Natural Language Processing, Search Algorithms, Regression models
etc. basically I want to design some sort of games to explain how different algorithms
works.
Let's see an Example: 🔎
Greedy Best First Algorithm - Interactive Explanation Demo
For some moments Stop thinking 🤔 about any algorithms and look at this diagram: 👇
1st
Suppose, you’re travelling from your office to your home and you want to reach as soon as possible, then which path will
you choose? Think for a while. 🤔
Ok, now let's look at the next diagram: 👇
2nd
If I’m not wrong, you might have thought about this path, which seems the shortest among all, right?
If it is right then you’ve just tried to be greedy. 💰
In this way, we as a human, decide which case/path is best for us. Now let's think from an computer's perspective.
I think you all have played Counter Strike! **Have you ever wondered how an enemy agent finds the location of the player in the
Game World? **
This is where Algorithms comes into play. In games, Best-first search may be used as a path-finding algorithm for game characters.
For a better understanding of Greedy Best First Search Algorithm, I've created a basic interactive game which you might want to play to have
a better understanding. Head over to this link and scroll down to find the game.
Planning for future:
As of now, I've only created the visualization for Greedy Best Search Algorithm. So I'm planning to create more visualization to certain
search algorithms like: Dijkstra's Algorithm, A* Algorithm, Depth First Search, Breadth First Search and some Machine Algorithms like
Linear Regression etc.
About
A new way of learning Algorithms.
souravinsights.github.io/LearnAlgorithm/
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alogrithmshactoberfestinteractive-visualizationsvisualization
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