Forwarded from Tech World
Finally i deployed lesson of the day bot on python anywhere.
π What can Lesson Of The Day Bot do:
π Show todayβs lesson instantly.
π° Browse through past lessons easily.
π Bookmark and revisit lessons you like.
π Search by date.
π @lesson_of_day_bot
here is the Github repo https://github.com/Lidiya-Bokona/Lesson_of_the_day_bot.git
#project
π What can Lesson Of The Day Bot do:
π Show todayβs lesson instantly.
π° Browse through past lessons easily.
π Bookmark and revisit lessons you like.
π Search by date.
π @lesson_of_day_bot
here is the Github repo https://github.com/Lidiya-Bokona/Lesson_of_the_day_bot.git
#project
β€8
Tech World
Photo
This is cool guysπ₯ Let's show her some love guys go and star her repo on github.
@byte_philosopher
@byte_philosopher
β€4π₯1πΎ1
#August_25_LeetCode_Grid
π Backtracking in DSA β Quick Recap
Backtracking is like exploring all paths in a maze. You try options, go forward, and undo your choices if they donβt work.
How it works:
Choose: Pick a possible option.
Explore: Move forward recursively with that choice.
Backtrack: Undo the choice to try other possibilities.
β Key idea: Explore all possibilities systematically, but prune paths that fail early.
β Use cases:
Subsets & permutations
Combination sum problems
Sudoku & N-Queens
Maze & pathfinding problems
π‘ 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
π Backtracking in DSA β Quick Recap
Backtracking is like exploring all paths in a maze. You try options, go forward, and undo your choices if they donβt work.
How it works:
Choose: Pick a possible option.
Explore: Move forward recursively with that choice.
Backtrack: Undo the choice to try other possibilities.
β Key idea: Explore all possibilities systematically, but prune paths that fail early.
β Use cases:
Subsets & permutations
Combination sum problems
Sudoku & N-Queens
Maze & pathfinding problems
π‘ 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
π₯3β‘1π1π₯°1π1
This days what I understand from solving leetcode is, you always have to think in the reverse way. (ααα₯α¦ αα°α₯π ) is the better way.
For ex: if your first thought for the solution was addition then use substraction boom it worksπ
@byte_philosopher
For ex: if your first thought for the solution was addition then use substraction boom it worksπ
@byte_philosopher
π―4π1π1
#August_26_LeetCode_Grid
π Heap: The King of Efficiency π
Ever wondered how to always grab the biggest or smallest number FAST? β‘
Thatβs where Heaps come in!
π₯ Whatβs a Heap?
A tree-like structure π
Min-Heap β smallest on top (root).
Max-Heap β largest on top (with a trick in Python π).
β‘ Why are they cool?
π Always gives you the top element in O(1) time.
β Insert / β Remove in O(log n).
Used in priority queues, scheduling, Dijkstraβs algorithm, and finding kth largest/smallest element!
π Python Example:
π‘ Remember:
Heaps donβt fully sort data, they just keep the top element ready at all times π.
βοΈ Next time you need efficiency β Just call the Heap King π
@byte_philosopher
π Heap: The King of Efficiency π
Ever wondered how to always grab the biggest or smallest number FAST? β‘
Thatβs where Heaps come in!
π₯ Whatβs a Heap?
A tree-like structure π
Min-Heap β smallest on top (root).
Max-Heap β largest on top (with a trick in Python π).
β‘ Why are they cool?
π Always gives you the top element in O(1) time.
β Insert / β Remove in O(log n).
Used in priority queues, scheduling, Dijkstraβs algorithm, and finding kth largest/smallest element!
π Python Example:
import heapq
nums = [5, 2, 8, 3, 1]
heapq.heapify(nums) # min-heap
print(nums[0]) # π 1 (smallest)
# max-heap trick
nums = [-x for x in nums]
heapq.heapify(nums)
print(-nums[0]) # π 8 (largest)
π‘ Remember:
Heaps donβt fully sort data, they just keep the top element ready at all times π.
βοΈ Next time you need efficiency β Just call the Heap King π
@byte_philosopher
β€2π₯1
Forwarded from kin
Introducing ExyRead β your all in one AI powered reading companion
After months of building, Iβm 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 β ask questions, get instant support
One-click PDF summaries β save time, grasp key points faster
Note-taking β write down ideas while studying
AI note summaries β turn long notes into short takeaways
Instant explanations β highlight text and get AI-powered clarity
Progress tracking β stay motivated as you read
Smart organization β create folders to manage files easily
Study reminders β never miss your next session
Your feedback will play a big role in shaping the future of the app.
π‘ Be one of the first to try it here.
#my_project
@kintechno
After months of building, Iβm 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 β ask questions, get instant support
One-click PDF summaries β save time, grasp key points faster
Note-taking β write down ideas while studying
AI note summaries β turn long notes into short takeaways
Instant explanations β highlight text and get AI-powered clarity
Progress tracking β stay motivated as you read
Smart organization β create folders to manage files easily
Study reminders β never miss your next session
Your feedback will play a big role in shaping the future of the app.
π‘ Be one of the first to try it here.
#my_project
@kintechno
π5π₯3π2
Forwarded from Orthodox Spirituality
βLet 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.β
+Abba Moses
+Abba Moses
β€5
#August_27_28_29_LeetCode_Grind
HashMaps (Python dict) Recap
A HashMap stores data in keyβvalue pairs for super-fast access β‘.
Think of it like a dictionary π: words = keys, meanings = values.
β Key Features:
Fast lookups, inserts, deletes β O(1) average
Keys are unique
Perfect for counting, mapping & caching
π₯ Use Cases:
βοΈ Word frequency counters
βοΈ Caching results
βοΈ Graph adjacency lists
@byte_philosopher
HashMaps (Python dict) Recap
A HashMap stores data in keyβvalue pairs for super-fast access β‘.
Think of it like a dictionary π: words = keys, meanings = values.
β Key Features:
Fast lookups, inserts, deletes β 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"] # deleteπ₯ Use Cases:
βοΈ Word frequency counters
βοΈ Caching results
βοΈ Graph adjacency lists
@byte_philosopher
π₯5π3
#August_30_LeetCode_Grid
π Graphs in DSA
A Graph = π’ Nodes (called vertices) + π Connections (called edges).
Theyβre everywhere β social networks, maps, recommendations, even computer networks!
Types of Graphs:
Directed vs Undirected β‘οΈ / βοΈ
Weighted vs Unweighted βοΈ
Cyclic vs Acyclic π / π«
Ways to Store Graphs:
Adjacency List β (efficient)
Adjacency Matrix π² (easy but heavy)
Popular Graph Algorithms:
BFS (Breadth-First Search) π level by level
DFS (Depth-First Search) π go deep first
Dijkstra π£οΈ shortest path
Kruskal & Prim π minimum spanning tree
π Mastering graphs = mastering real-world problem solving.
@byte_philosopher
π Graphs in DSA
A Graph = π’ Nodes (called vertices) + π Connections (called edges).
Theyβre everywhere β social networks, maps, recommendations, even computer networks!
Types of Graphs:
Directed vs Undirected β‘οΈ / βοΈ
Weighted vs Unweighted βοΈ
Cyclic vs Acyclic π / π«
Ways to Store Graphs:
Adjacency List β (efficient)
Adjacency Matrix π² (easy but heavy)
Popular Graph Algorithms:
BFS (Breadth-First Search) π level by level
DFS (Depth-First Search) π go deep first
Dijkstra π£οΈ shortest path
Kruskal & Prim π minimum spanning tree
π Mastering graphs = mastering real-world problem solving.
@byte_philosopher
π4β€1π₯1π₯°1