#August_21_22_23LeetCode_Grid
🌳 Trees in Data Structures 🌳
Think of a Tree like a family tree or folder system:
🌱 Root → the starting point
🌿 Branches (children) → connect to other nodes
🍂 Leaves → end nodes with no children
✨ Popular Trees:
🌲 Binary Tree → max 2 children per node
🔎 Binary Search Tree (BST) → left < root < right
🏗 Heaps & Balanced Trees → used in priority queues, databases
⚡ Why Learn Trees?
✔ Organize data efficiently
✔ Fast search & sorting
✔ Used in file systems, AI, compilers, HTML DOM
📌 Next time you open folders on your PC… you’re walking through a tree 🌳😉
@byte_philosopher
I finished my study on trees here is the short summery
🌳 Trees in Data Structures 🌳
Think of a Tree like a family tree or folder system:
🌱 Root → the starting point
🌿 Branches (children) → connect to other nodes
🍂 Leaves → end nodes with no children
✨ Popular Trees:
🌲 Binary Tree → max 2 children per node
🔎 Binary Search Tree (BST) → left < root < right
🏗 Heaps & Balanced Trees → used in priority queues, databases
⚡ Why Learn Trees?
✔ Organize data efficiently
✔ Fast search & sorting
✔ Used in file systems, AI, compilers, HTML DOM
📌 Next time you open folders on your PC… you’re walking through a tree 🌳😉
@byte_philosopher
❤5
Forwarded from Tech World
Finally i deployed lesson of the day bot on python anywhere.
🔎 What can Lesson Of The Day Bot do:
📘 Show today’s lesson instantly.
🕰 Browse through past lessons easily.
🔖 Bookmark and revisit lessons you like.
📅 Search by date.
👉 @lesson_of_day_bot
here is the Github repo https://github.com/Lidiya-Bokona/Lesson_of_the_day_bot.git
#project
🔎 What can Lesson Of The Day Bot do:
📘 Show today’s lesson instantly.
🕰 Browse through past lessons easily.
🔖 Bookmark and revisit lessons you like.
📅 Search by date.
👉 @lesson_of_day_bot
here is the Github repo https://github.com/Lidiya-Bokona/Lesson_of_the_day_bot.git
#project
❤8
Tech World
Photo
This is cool guys🔥 Let's show her some love guys go and star her repo on github.
@byte_philosopher
@byte_philosopher
❤4🔥1👾1
#August_25_LeetCode_Grid
🚀 Backtracking in DSA – Quick Recap
Backtracking is like exploring all paths in a maze. You try options, go forward, and undo your choices if they don’t work.
How it works:
Choose: Pick a possible option.
Explore: Move forward recursively with that choice.
Backtrack: Undo the choice to try other possibilities.
✅ Key idea: Explore all possibilities systematically, but prune paths that fail early.
✅ Use cases:
Subsets & permutations
Combination sum problems
Sudoku & N-Queens
Maze & pathfinding problems
💡 Tips:
Always have a base case to stop recursion.
Make sure to undo changes before returning to explore other options.
Example in LeetCode: Combination Sum, Subsets, N-Queens
@byte_philosopher
🚀 Backtracking in DSA – Quick Recap
Backtracking is like exploring all paths in a maze. You try options, go forward, and undo your choices if they don’t work.
How it works:
Choose: Pick a possible option.
Explore: Move forward recursively with that choice.
Backtrack: Undo the choice to try other possibilities.
✅ Key idea: Explore all possibilities systematically, but prune paths that fail early.
✅ Use cases:
Subsets & permutations
Combination sum problems
Sudoku & N-Queens
Maze & pathfinding problems
💡 Tips:
Always have a base case to stop recursion.
Make sure to undo changes before returning to explore other options.
Example in LeetCode: Combination Sum, Subsets, N-Queens
@byte_philosopher
🔥3⚡1👍1🥰1👏1
This days what I understand from solving leetcode is, you always have to think in the reverse way. (ገልብጦ ማሰብ😁 ) is the better way.
For ex: if your first thought for the solution was addition then use substraction boom it works😁
@byte_philosopher
For ex: if your first thought for the solution was addition then use substraction boom it works😁
@byte_philosopher
💯4👏1👌1
#August_26_LeetCode_Grid
👑 Heap: The King of Efficiency 👑
Ever wondered how to always grab the biggest or smallest number FAST? ⚡
That’s where Heaps come in!
🔥 What’s a Heap?
A tree-like structure 📚
Min-Heap → smallest on top (root).
Max-Heap → largest on top (with a trick in Python 😉).
⚡ Why are they cool?
📍 Always gives you the top element in O(1) time.
➕ Insert / ❌ Remove in O(log n).
Used in priority queues, scheduling, Dijkstra’s algorithm, and finding kth largest/smallest element!
🐍 Python Example:
💡 Remember:
Heaps don’t fully sort data, they just keep the top element ready at all times 🚀.
⚔️ Next time you need efficiency → Just call the Heap King 👑
@byte_philosopher
👑 Heap: The King of Efficiency 👑
Ever wondered how to always grab the biggest or smallest number FAST? ⚡
That’s where Heaps come in!
🔥 What’s a Heap?
A tree-like structure 📚
Min-Heap → smallest on top (root).
Max-Heap → largest on top (with a trick in Python 😉).
⚡ Why are they cool?
📍 Always gives you the top element in O(1) time.
➕ Insert / ❌ Remove in O(log n).
Used in priority queues, scheduling, Dijkstra’s algorithm, and finding kth largest/smallest element!
🐍 Python Example:
import heapq
nums = [5, 2, 8, 3, 1]
heapq.heapify(nums) # min-heap
print(nums[0]) # 👉 1 (smallest)
# max-heap trick
nums = [-x for x in nums]
heapq.heapify(nums)
print(-nums[0]) # 👉 8 (largest)
💡 Remember:
Heaps don’t fully sort data, they just keep the top element ready at all times 🚀.
⚔️ Next time you need efficiency → Just call the Heap King 👑
@byte_philosopher
❤2🔥1
Forwarded from kin
Introducing ExyRead – your all in one AI powered reading companion
After months of building, I’m excited to share that 90% of the core features are now complete!
ExyRead is designed to support students and anyone who wants to make their reading and studying smarter and easier.
Key Features:
AI Chat – ask questions, get instant support
One-click PDF summaries – save time, grasp key points faster
Note-taking – write down ideas while studying
AI note summaries – turn long notes into short takeaways
Instant explanations – highlight text and get AI-powered clarity
Progress tracking – stay motivated as you read
Smart organization – create folders to manage files easily
Study reminders – never miss your next session
Your feedback will play a big role in shaping the future of the app.
💡 Be one of the first to try it here.
#my_project
@kintechno
After months of building, I’m excited to share that 90% of the core features are now complete!
ExyRead is designed to support students and anyone who wants to make their reading and studying smarter and easier.
Key Features:
AI Chat – ask questions, get instant support
One-click PDF summaries – save time, grasp key points faster
Note-taking – write down ideas while studying
AI note summaries – turn long notes into short takeaways
Instant explanations – highlight text and get AI-powered clarity
Progress tracking – stay motivated as you read
Smart organization – create folders to manage files easily
Study reminders – never miss your next session
Your feedback will play a big role in shaping the future of the app.
💡 Be one of the first to try it here.
#my_project
@kintechno
👍5🔥3👏2
Forwarded from Orthodox Spirituality
“Let us acquire reverence, dignity, and meekness towards all people, as well as precise knowledge of them. so that we may be able to avoid familiarity, which is the mother of all evils.”
+Abba Moses
+Abba Moses
❤5
#August_27_28_29_LeetCode_Grind
HashMaps (Python dict) Recap
A HashMap stores data in key–value pairs for super-fast access ⚡.
Think of it like a dictionary 📖: words = keys, meanings = values.
✅ Key Features:
Fast lookups, inserts, deletes → O(1) average
Keys are unique
Perfect for counting, mapping & caching
🔥 Use Cases:
✔️ Word frequency counters
✔️ Caching results
✔️ Graph adjacency lists
@byte_philosopher
HashMaps (Python dict) Recap
A HashMap stores data in key–value pairs for super-fast access ⚡.
Think of it like a dictionary 📖: words = keys, meanings = values.
✅ Key Features:
Fast lookups, inserts, deletes → O(1) average
Keys are unique
Perfect for counting, mapping & caching
hashmap = {"apple": 2, "banana": 5}
print(hashmap["apple"]) # 2
hashmap["banana"] = 10 # update
hashmap["grape"] = 7 # insert
del hashmap["apple"] # delete🔥 Use Cases:
✔️ Word frequency counters
✔️ Caching results
✔️ Graph adjacency lists
@byte_philosopher
🔥5👍3