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ONBFS vs DFS in Maze
@onjsdev
#Graph Bfs Dfs Visualization
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GHDepth-First Search (DFS) and Breadth-First Search (BFS)
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Let's dive into the details of Depth-First Search (DFS) and Breadth-First Search (BFS), two fundamental algorithms used in data structures and AI.
Depth-First Search (DFS)
DFS is a traversal algorithm that explores a graph or tree by visiting a node and then visiting all of its neighbors before backtracking.
How DFS Works:
1. Choose a starting node: Select a node to begin the search.
2. Explore neighbors: Visit all the neighbors of the current node.
3. Backtrack: Return to the previous node and explore its unvisited neighbors.
4. Repeat: Continue this process until all nodes are visited.
Types of DFS:
1. Pre-order DFS: Visit the current node before its neighbors.
2. In-order DFS: Visit the current node between its neighbors.
3. Post-order DFS: Visit the current node after its neighbors.
Applications of DFS:
1. Topological sorting: Ordering the nodes in a directed acyclic graph (DAG).
2. Finding connected components: Identifying connected subgraphs in an undirected graph.
3. Testing whether a graph is connected: Determining if a graph has a path between every pair of nodes.
Breadth-First Search (BFS)
BFS is a traversal algorithm that explores a graph or tree by visiting all the nodes at the current level before moving on to the next level.
How BFS Works:
1. Choose a starting node: Select a node to begin the search.
2. Explore neighbors: Visit all the neighbors of the current node.
3. Move to the next level : Visit all the nodes at the next level.
4. Repeat: Continue this process until all nodes are visited.
Types of BFS:
1. Level-order BFS: Visit all nodes at the current level before moving to the next level.
2. Shortest-path BFS: Find the shortest path between two nodes.
Applications of BFS:
1. Finding the shortest path: Determining the minimum number of edges between two nodes.
2. Minimum spanning tree: Finding the subset of edges that connect all nodes with minimum total weight.
3. Web crawlers: Traversing the web graph to index web pages.
#datastructure #coding #programming #python #computerscience #coder #javascript #java #programmer
@ghazi_it
32.4K
COGraphs Part-2: From Theory to Mastery! 🕸️
Now that you’ve got the basics down, let’s dive deeper into advanced Graph concepts like BFS, DFS, and Dijkstra’s Algorithm! 🚀
In this reel, I’ll walk you through these critical algorithms with step-by-step breakdowns and visuals that’ll help you tackle even the toughest graph problems with ease! 💡
Want the exclusive Graphs Part-2 Notes to level up your coding game?
Comment ‘Link’ and I’ll send you the notes to take your Graph skills to the next level! 💪
Let’s conquer Graphs together, one algorithm at a time! 🌐
👉 Follow @codewithsantosh for more tutorials, coding tips, and algorithm deep dives!
#dsa #graphs #algorithms #bfs #dfs #coding #interviewprep #codewithsantosh #interviewcafenotes
@codewithsantosh
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SABFS 🏹, Comment “Graph” ❤️
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@samitknows
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BIBFS is a graph traversal algorithm that explores all nodes at a given depth before moving to the next level. It's often used to find the shortest path between two nodes in a graph where all edges have the same weight (e.g., unweighted graphs).
#algorithm #computer science #coding #programming #datastructures #algorithms #softwaredevelopment #technology
#codinglife #developer #programmer #programmingtips #codingtutorial
#bfs #breadthfirstsearch #graphalgorithms #graph theory #traversal #dfs #depthfirstsearch
#tree #treealgorithms #binarytree #binarysearchtree #graphvisualization #visualization
@bijesh_chaurasia
23.9K
GR"Unlocking Insights: Explore the Power of Graphs!"
#GraphAnalytics
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@greenscreenai
1.3M
CHJust because you can make your chart look unique, doesn't mean you should. A good data visualization is about clarity, not just creativity. When every element - color, font, and shape - works against readability, you're not improving the story, you're burying it. Radial bar charts, for example, may look visually compelling, but they aren't always the best tool. While they do okay in displaying cyclical data, such as seasonal trends or annual sales patterns, their complexity can make your point harder to understand in other contexts.
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@chartosaur
176
CODay 3 of #100DaysOfCode: DFS Graph Traversal 🌲
DFS = Depth First Search. Go deep before going wide.
Core idea:
1. Use Stack or Recursion + Visited array
2. Start at source, explore one neighbor fully before backtracking
3. Recursion makes it clean, stack makes it iterative
BFS vs DFS quick take:
- BFS → Shortest path, level order, uses Queue
- DFS → Path finding, cycle detection, uses Stack/Recursion
- Both: O(V + E) time, O(V) space
Built this on the same Adjacency List from Day 1. Recursion finally feels less scary.
Comment "code" and I'll send you the Java DFS code 👇
#graph #LeetCode #Java #DSA
@code_with_ink
672
PY¿Explorar por niveles o ir a fondo? Te explico BFS y DFS, sus mecánicas, complejidad y cuándo usar cada uno. #DataScience #Algoritmos #Grafos #BFS #DFS #Programacion #Python #ComputerScience #TechTok
@pypromx
61.2K
PHStop suffering in silence. These tools will level up your analysis game!
Which one’s your fav?
Comment down👇🏻
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@phdwithanjali
334
DA🏍️ Built a full Sales Intelligence Dashboard in just 5 minutes using Claude AI!
I took a raw Honda sales dataset (1,500 records) and asked Claude AI to build a complete BI dashboard — no coding experience needed.
Here's what it includes:
✅ 5 KPI Cards — Total Sales, Profit, Orders, Avg Order Value & Customer Rating
📈 Monthly Sales Trend — Line chart with Sales vs Profit
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Everything updates dynamically when you click any filter — just like Power BI or Tableau!
Tech used: HTML + CSS + JavaScript + Chart.js — all in ONE file, runs directly in the browser.
The best part? I just uploaded my CSV and gave a prompt. Claude handled the data aggregation, chart logic, color design, and responsive layout — all by itself.
🤖 AI is not replacing analysts. It's giving them superpowers.
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@data_withharry
29.6K
FOFVG entry confirmation #orderflow #fyp #fvg #heatmap #footprintchart
@fostermanshq
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