Improving Model Evaluation Skills with Python & Data Science

🚀 Day 22 – 100 Days of Python & Data Science Today, I focused on feature selection and understanding how different features impact model performance. Learning that better features = better models. Improving step by step 💻✨ #100DaysOfPython #DataScience #MachineLearning #Python #LearningJourney 💻GitHub: https://lnkd.in/dUG6qvk5

🚀 Just went through a NumPy Crash Course — and one thing is clear: 👉 NumPy is the foundation of data analytics & data science in Python. From arrays to indexing, slicing, and functions like arange() — everything starts here. 💡 Master NumPy, and the rest becomes much easier. Still learning, still growing. #DataAnalytics #Python #NumPy #LearningJourney

🚀 Day 24 – 100 Days of Python & Data Science Today I practiced data preprocessing and cleaning — an important step before building any Machine Learning model. Clean data leads to better analysis and better results. Learning and improving every day 💻✨ #100DaysOfPython #DataScience #Python #MachineLearning 💻GitHub:https://lnkd.in/dUG6qvk5

📅 Day 6/30 — Building a “Pages You Might Like” Feature Continuing my 30-day journey into data science, today I built a basic version of the “Pages You Might Like” feature using pure Python. What I worked on today: 📄 Understanding user interests and page data 🔍 Finding patterns based on user preferences ⚙️ Using loops, conditions, and dictionaries to process data 💡 Generating simple page recommendations It was interesting to see how recommendation features can be created using core Python logic without relying on external libraries. ➡️ Next step: exploring more ways to analyze datasets using Python. #LearningInPublic #Python #Anaconda #JupyterNotebook #DataScience #30DaysOfLearning #ProgrammingJourney

📊 What I learned this week in Data Science This week, I explored: • Basics of Python for data analysis • How pandas helps clean and analyze datasets • Why data cleaning is more important than modeling Still learning step by step, but enjoying the process 🚀 #DataScience #Python #LearningInPublic #ComputerEngineering

🚀 Day 2 – Data Science Learning Journey Today’s session was all about Matplotlib, one of the most important libraries for data visualization in Python. I explored various functions used to create different types of graphs and plots. It was really interesting to see how raw data can be transformed into meaningful visual insights, making patterns and trends much easier to understand. Every step in this journey is helping me understand how data tells a story through visualization. 📊 #DataScience #Python #Matplotlib #DataVisualization #LearningJourney

Bridging the gap between mathematical theory and Python execution. 🚀 Today's session was all about balance: building intuition with hand-solved equations on paper, and then translating that logic into Python code on my screen. I firmly believe that a strong mathematical foundation is the real engine behind every good Data Scientist. Slowly but surely chipping away at the goals. One step, one logical block, and one cleared backlog at a time. The August target is set! 💻📈 #DataScience #PythonProgramming #Consistency #TechJourney #GrowthMindset #DataScience #Python #TechTransition #LearningInPublic #MasaiSchool #IITMandi #CareerJourney #DataScientist #CodingJourney #CodeLogic

🚀 Day 23 – 100 Days of Python & Data Science Today I practiced data visualization to better understand patterns and relationships in datasets. Visualizing data makes analysis more clear and meaningful. Learning a little more every day 💻✨ #100DaysOfPython #DataScience #Python #LearningJourney 💻GitHub:https://lnkd.in/dUG6qvk5