Nexus Global Inv

Somos un club de inversión que mezcla el análisis técnico y fundamental. Buscamos buenas empresas a un buen precio.

[Electrical Knowledge @electric_4u]

How a swiich mode power supply works

[TIC Educativas💻📱 @TicEducativas]

¿Abrumado por tantas opciones de IA? 🤯 No busques la "mejor", busca la que mejor se adapte a tu necesidad pedagógica o profesional.

Desde la integración en Office hasta la potencia en idiomas o diseño, cada herramienta es un aliado distinto. ¡Elige con estrategia! 🚀

#EdTech #IA #InnovaciónEducativa #Productividad #TIC

Créditos Data Science

[Bayyoo @TheBayoHub]

Here's a simple 30-day roadmap to learn Python for Data Analytics.

Save this.

[Python Developer @PythonDvz]

If Computers Had Feelings Lol 😂

[Cryptoleakvn @cryptoleakvn]

🚀 Pi Network Is Among the Powerful Projects Emerging from Stanford University!

Pi Network is listed among the members of the Stanford Engineering Computer Science “Our Members” page, alongside some of the world’s largest technology companies.

Along with giants such as Google, Apple, Amazon, IBM, NVIDIA, and Meta, Pi Network’s presence highlights the strength of its vision and ecosystem.

This is a strong indication that Pi could play an important role in the future of financial and technological infrastructure. 💜

#PiNetwork #Stanford #Pi #Crypto #Web3 #GreatAwakening

[The codewali @the_codewala]

Every Vibe Coder out there ☠️

[Dhanian 🗯️ @e_opore]

What is Docker – Understanding Containers vs. Virtual Machines.

Grab the Docker Ebook: https://t.co/RH1xDtQtxv

[Espabila @ahorrayespabila]

Producto Interior Bruto. No mide la calidad de vida de un país, mide la capacidad productiva.

Mini Curso de Economía
Capítulo 3👇

[Juanlu_CabanillasGar @JuanluCaba_Unex]

📊 𝗩𝗮𝗹𝗼𝗿𝗲𝘀 𝗔𝘁𝗶́𝗽𝗶𝗰𝗼𝘀 (𝗢𝘂𝘁𝗹𝗶𝗲𝗿𝘀): 𝗣𝗲𝗾𝘂𝗲𝗻̃𝗼𝘀 𝗱𝗮𝘁𝗼𝘀, 𝗴𝗿𝗮𝗻𝗱𝗲𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝗲𝘀. 📊
En Ciencia de Datos, no todos los datos siguen el comportamiento esperado. Algunas observaciones se alejan significativamente.

[Skill Up Daily @LearnologyX]

Layout tools

[Learn Something @cooltechtipz]

Evolution of sequence models in deep learning.

[Brij Pandey @LearnWithBrij]

LeetCode felt impossible...

Until I realized most coding interviews are built around the SAME patterns.

Master these 15 patterns, and you'll solve 80%+ of interview questions faster 👇

1️⃣ Prefix Sum

Use when:
→ range sum queries
→ cumulative calculations

Common problems:
• Subarray Sum Equals K
• Range Sum Query

2️⃣ Two Pointers

Use when:
→ searching pairs
→ sorted arrays
→ removing duplicates

Common problems:
• Two Sum II
• Container With Most Water

3️⃣ Sliding Window

Use when:
→ subarrays
→ substrings
→ fixed/variable windows

Common problems:
• Longest Substring Without Repeating Characters
• Maximum Average Subarray

4️⃣ Fast & Slow Pointers

Use when:
→ cycle detection
→ linked lists
→ middle element problems

Common problems:
• Linked List Cycle
• Happy Number

5️⃣ In-Place Linked List Reversal

Use when:
→ reversing nodes
→ reordering linked lists

Common problems:
• Reverse Linked List
• Reverse Nodes in K-Group

6️⃣ Monotonic Stack

Use when:
→ next greater element
→ histogram problems
→ range optimization

Common problems:
• Daily Temperatures
• Largest Rectangle in Histogram

7️⃣ Top K Elements

Use when:
→ highest frequency
→ largest/smallest K items

Tools:
→ Heap
→ Priority Queue

Common problems:
• Top K Frequent Elements
• K Closest Points

8️⃣ Overlapping Intervals

Use when:
→ scheduling
→ merging ranges
→ meeting rooms

Common problems:
• Merge Intervals
• Meeting Rooms

9️⃣ Modified Binary Search

Use when:
→ sorted data
→ search optimization
→ rotated arrays

Common problems:
• Search in Rotated Sorted Array
• First Bad Version

🔟 Binary Tree Traversal

Master:
→ Preorder
→ Inorder
→ Postorder

Foundation for nearly all tree

1️⃣1️⃣ Depth-First Search (DFS)

Use when:
→ exploring paths
→ recursion
→ graph traversal

Common problems:
• Number of Islands
• Path Sum

1️⃣2️⃣ Breadth-First Search (BFS)

Use when:
→ shortest path
→ level-order traversal

Common problems:
• Binary Tree Level Order Traversal
• Rotting Oranges

1️⃣3️⃣ Matrix Traversal

Use when:
→ grids
→ 2D graphs
→ island problems

Common problems:
• Flood Fill
• Word Search

1️⃣4️⃣ Backtracking

Use when:
→ permutations
→ combinations
→ decision trees

Common problems:
• N-Queens
• Subsets
• Combination Sum

1️⃣5️⃣ Dynamic Programming

The pattern everyone fears.

Master:
→ Memoization
→ Tabulation
→ State Transitions

Common problems:
• House Robber
• Longest Increasing Subsequence
• Knapsack

Most interview candidates memorize solutions.

Top candidates recognize patterns.

The question changes.

The pattern doesn't.

Learn the pattern once.
Solve hundreds of problems.

📌 Save this roadmap

💬 Which pattern took you the longest to master?

♻️ Repost to help someone preparing for coding interviews

#LeetCode #DSA #CodingInterview #Algorithms #Programming #SoftwareEngineering #TechCareer

[NextLevelBiz @NextLevelBiz]

12 Atomic Habits That Will Change Your Life Forever

[Adrian _Ai💡 @adrian_aiking]

Strategic Thinking - Master Complexity, Command Clarity, Own the Future.

Follow @adrian_aiking for more!

[Knowledge Nexus @Xp_Logs]

Barcodes are not just a random number.

[𝐇𝐚𝐦𝐳𝐚 | Network Engineer (Aspiring) @Hamzaonchain]

SMALL OFFICE SETUP

[Edgar C Francis @edgarcfrancis]

What is Link Layer Discovery Protocol (LLDP)? https://t.co/lKLshuHNKu