Python Revision: Modules & Machine Learning Essentials

Day 61 – File Reading in Python: Day 61 focused on reading files in Python using different approaches. I practiced opening a file, reading its contents, and managing resources using both the traditional open–close method and the with statement. This helped strengthen my understanding of file handling basics and writing safer, cleaner, and more efficient file operations in Python. GitHub Code: https://lnkd.in/geEDgvc9 #Day61 #100DaysOfCode #Python #FileHandling #LearningPython #CodingJourney #DailyCoding #Consistency

LeetCode #98 – Validate Binary Search Tree | Python Implementation I implemented a recursive DFS approach with boundary tracking to validate BST properties. Core Insight: BST validation requires tracking allowable ranges, not just comparing immediate children. Each recursive call narrows the valid interval, ensuring global ordering throughout the entire subtree. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinarySearchTree #Recursion #DFS #CodingInterview #SoftwareEngineering

📌Python Sets – Accessing Set Items I learned how to access elements in a Python set using a loop. Since sets are unordered, we cannot access items using an index. Instead, we use a for loop to iterate through each element. ✅ Sets do not support indexing ✅ Items are accessed using loops ✅ Order of output may change ✅ Duplicate values are automatically removed #Python #DataAnalytics #LearningJourney #PythonSets #CodingPractice #Upskilling

I just published my article on Python Dictionaries. In this blog, I explained: ✔ what dictionaries are ✔ how key–value pairs work ✔ simple Python examples ✔ real-life uses like phone book, student records & inventory systems This topic helped me understand how real applications store and manage data. Thank you @Innomatics Research Labs for encouraging practical learning. 👉 Read here: https://lnkd.in/g7WGamc2 😊 Innomatics Research Labs #Python #Programming #DataStructures #Coding #EDA

Day 15 of Python Learning 💻🐍 Today’s focus: input() and print() functions 🐍 These core concepts make programs interactive and meaningful. Building strong fundamentals, one day at a time. Consistency over everything. #Python #LearningPython #PythonBasics #CodingJourney #100DaysOfCode

Day 65 – Counting Words in a File Using Python: Day 65 focused on counting the number of words in a text file using Python. I practiced reading file content, splitting the text into words, and calculating the total count using both the traditional file handling method and the with statement. This exercise strengthened my understanding of file reading, string operations, and writing simple logic to analyze text data efficiently. GitHub Code: https://lnkd.in/gWxV_Uxb #Day65 #100DaysOfCode #Python #FileHandling #LearningPython #CodingJourney #DailyCoding #Consistency

Strings are everywhere in Python - file names, user input, APIs, data cleaning, logs. If you work with Python, these 10 string methods aren’t optional — they’re daily tools. You’ll use them for: - cleaning extra spaces. - checking file extensions. - splitting and joining data. - finding and counting characters. These methods help you write cleaner, shorter, and more readable code. If you ever forget the syntax, this one image is enough to refresh your memory. 📌 Save it — future you will thank you. #Python #LearnPython #PythonTips #Programming #Coding #SoftwareEngineering #PythonDeveloper

📅 Day 22 of Learning Python – Matrices 🧮 Today, I explored Matrices in Python using lists. A matrix is simply a list of lists, commonly used to represent: Rows & Columns Real-world data like scores, images, etc. 📌 Key Learnings: Indexing starts from 0 l[i] gives a full row l[i][j] gives a single element Nested loops help traverse rows and columns Feeling more confident with loops + matrices today 💪 Step by step, moving forward 🚀 #Python #LearningPython #Matrices #CodingJourney #Day22 #ProgrammingBasics #Consistency

Python 3 isn’t just an upgrade — it’s the standard. All modern libraries in Data Science, Machine Learning, and AI are built for Python 3. If you’re still learning Python, start with Python 3. There’s no reason to go backward. #Python #Python3 #DataScience #MachineLearning #Programming #TechLearning #CareerGrowth

Python Foundations 2026 – Part 7 Functions are what turn messy code into clean, reusable logic. In Part 7 of our Python Foundations series, we explore: • What functions are • Why they matter • How to define and use them • Understanding parameters and return If you can write functions, you can structure real Python programs. Learn more: https://lnkd.in/ejuVfi2c Python lessons → Wednesdays Other tech articles → Mondays Next up: A mini Python project. #Python #LearnToCode #Programming #BeginnersInTech #TechEducation #Python2026 #JMSM #KNKA