🚀 Excited to connect with people interested in AI · Data Science! I’m an MTech student in AI & DS, sharing my daily learnings + side-projects here. Looking to collaborate, learn and grow. 🔍 Open to internship / part-time roles 📬 DMs open | Let’s build together! #connection
Me: trains model for 2 hours Model: “Accuracy = 51%” Bro… that’s just guessing 😭 #MachineLearning #AI
MTech mid-terms ongoing… Currently trying to find the mode of correct answers I can write. Spoiler: it’s close to zero 😂 #Exams #MTech #Stats #humor
👉 Two datasets can have the same mean & variance but look different when plotted. That’s why: 🔹Central Tendency & Dispersion aren’t enough 🔹Visualization reveals hidden structure 🔹Distances show how points actually relate #DataScience #MachineLearning #AI #LearnInPublic
🗓 Day 3: Learning Data Science 💎Scatter Plots 💎Cluster, Data Matrix 💎Dissimilarity for nominal, binary, and ordinal attributes 💎Euclidean, Manhattan, Minkowski distances 💎Cosine Similarity #learninginpublic #datascience #math
🗓 Day 2: Learning Data Science 💎 Measures of Central Tendency ✏️ Mean, Median, Mode, Midrange 💎 Dispersion ✏️ Range, Quantiles, Quartiles, 5-number summary, variance, standard deviation. 💎 Visualization ✏️ Boxplot, Quantile–Quantile Plot #learninginpublic #datascience
📖 Data Mining: Concepts and Techniques I am following this book for leaning Data Science. So far I found it easy to read and learn. What data science resources do you guys follow? Comment below 👇 #datascience #LearnInPublic #resources
🗓 Day 2: Learning Data Science 💎 Measures of Central Tendency ✏️ Mean, Median, Mode, Midrange 💎 Dispersion ✏️ Range, Quantiles, Quartiles, 5-number summary, variance, standard deviation. 💎 Visualization ✏️ Boxplot, Quantile–Quantile Plot #learninginpublic #datascience
🗓 Day 1: Learning Data Science 👉 Data and Datasets 👉 Types of Attributes 👉 General characteristics of Datasets #datascience #learning
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