Probability Foundations: Sample Space, Events, and Axioms

Day 23/100 – DSA Journey Problem: Remove Duplicates from Sorted Linked List A sorted linked list keeps duplicates next to each other, which makes it easy to remove them in one pass. Used simple traversal and pointer updates to skip duplicate nodes without extra space. Key Learning: Always use the structure of the data to simplify the solution. #Day23 #100DaysOfCode #DSA #LinkedList #Python #LeetCode

Back to consistency 💻🚀 Recently, I worked on implementing Pascal’s Triangle in Python — and it turned out to be a great exercise in logic building. While solving this, I learned: 🔹 How each row depends on the previous one 🔹 Better understanding of nested loops 🔹 Using mathematical logic instead of brute force It’s interesting how such a simple-looking pattern involves deeper thinking behind the scenes. Here’s my implementation 👇 Small steps like these are helping me build a strong foundation in Data Structures & Algorithms. #Python #DSA #CodingJourney #LearningInPublic #100DaysOfCode

Learn transfer learning with Python and Keras, including its applications, benefits, and implementation using popular libraries like Keras https://lnkd.in/gVDZSw9q #TransferLearningWithPython Read the full article https://lnkd.in/gVDZSw9q

Day 110 Same pattern, new constraint. #Day110 🧩 90. Subsets II How today went: • Very similar to the basic Subsets problem • First step: sort the array • While iterating, skip duplicate elements to avoid repeating subsets • Use the same backtracking pattern: append → recurse → pop What I learned: The core pattern stays the same — only the duplicate handling logic changes. This small condition makes a big difference. Backtracking is becoming more predictable now. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

Started my #30DaysOfPython journey today. 🚀 Here are some of the basics I picked up: 1. Python is a high-level, interpreted, open-source, object-oriented language created by Guido van Rossum. 2. Unlike many languages, Python uses indentation instead of curly brackets to define blocks of code. 3. I also revisited core data types like: (i) Numbers (ii) Strings (iii) Booleans (iv) Lists (v) Dictionaries (vi) Tuples (vii) Sets 4. One simple but useful thing: type() helps check the data type of any value. Day 1 done. One step closer to becoming more confident with Python. 🐍 #Python #30DaysOfPython #SoftwareDevelopment #LearningInPublic #CareerTransition

Python Clarity Series – Episode 25 Topic: Mutable vs Immutable Function Behavior 📌 Why did my list change after function call? def modify(lst): lst.append(100) a = [1, 2] modify(a) print(a) Output: [1, 2, 100] 👉 Lists are mutable → changes reflect outside Now: def modify(x): x = x + 10 a = 5 modify(a) print(a) Output: 5 👉 Integers are immutable → no change outside 💡 Rule: Mutable → changes persist Immutable → changes don’t This confusion causes logic errors. #PythonBasics #FunctionConcepts #StudentClarity #python #clarity

🚀 Day 3 — Python Journey Today’s focus was on float operations in Python (working with decimal numbers). 📌 What I learned: Float declaration Addition, subtraction, multiplication, division Rounding values using round() Scientific notation Precision handling in floats 💡 What I found interesting: Float values are not always 100% accurate due to precision limitations. Even simple calculations can sometimes give unexpected results. Understanding this early is important, especially for real-world applications like finance or data science. Step by step, trying to build a strong foundation. #Day3 #Python #CodingJourney #LearnInPublic #Consistency

Day 30/100 – #100DaysOfCode 🚀 Solved LeetCode #1299 – Replace Elements with Greatest Element on Right Side (Python). Today I practiced reverse traversal to efficiently replace each element with the greatest element on its right. Approach: 1) Initialize max_right = -1. 2) Traverse the array from right to left. 3) Store the current element in a temporary variable. 4) Replace the current element with max_right. 5) Update max_right as the maximum of max_right and the stored value. 6) Continue until the entire array is processed. Time Complexity: O(n) Space Complexity: O(1) Learning how reverse traversal can simplify problems efficiently 💪 #LeetCode #Python #DSA #Arrays #ProblemSolving #100DaysOfCode

Python Clarity Series – Episode 23 Topic: Floating Point Precision Issue 🤯 Why does this happen? print(0.1 + 0.2) Output: 0.30000000000000004 ❗ 👉 This is NOT a Python bug. It’s due to how floating-point numbers are stored in binary. 💡 Fix (when needed): round(0.1 + 0.2, 1) Output: 0.3 💡 Concept: Computers approximate decimal values internally. Important in: ✔ Financial calculations ✔ Data Science Don’t ignore this. #PythonConcepts #FloatingPoint #RealWorldCoding #python #clarity

Day 106 Some problems feel simple when the pattern clicks. #Day106 🧩 17. Letter Combinations of a Phone Number How today went: • Used a digit → letters map • Built combinations using backtracking • Maintained a string path at each step • One recursive call per choice — no need for complex state handling What I realized: Once you understand the pattern: → choose a letter → move to next digit → build the path Backtracking becomes very natural. Simple problem, but great for building confidence. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency