Welcome to the 100 Days of Machine Learning series — one of the most watched and most trusted and Evergreen Machine Learning playlists on Indian YouTube, followed by millions of learners who want to build a strong foundation in ML. This playlist is designed as a step-by-step roadmap to master Machine Learning, starting from the absolute basics and gradually moving toward advanced concepts and real-world implementation. Instead of jumping directly into code, the series focuses on building clear intuition, strong fundamentals, and practical understanding of how machine learning actually works. What you will learn in this series: • AI vs Machine Learning vs Deep Learning • Types of Machine Learning (Supervised, Unsupervised, Reinforcement Learning) • Data preprocessing and feature engineering • Exploratory Data Analysis (EDA) • Important ML algorithms (Regression, Classification, Clustering, etc.) • Model evaluation and validation techniques • Real-world ML workflow and best practices Each video covers a specific concept in a simple and structured way so you can build knowledge one step at a time, just like a 100-day learning roadmap. If you want to build a strong Machine Learning foundation for Data Science, AI, or ML Engineering, this playlist will guide you from beginner concepts to industry-level understanding. Notes: https://learnwith.campusx.in/s/store/courses/YouTube%20Notes
Curated by: CampusX (134 videos)
Decision Trees use metrics like Entropy and Gini Impurity to make split decisions. Entropy measures the disorder or randomness in a dataset, while Gini Impurity quantifies the probability of misclassifying a randomly chosen element. Information Gain, derived from these metrics, guides the tree in selecting the most informative features for optimal data splits, contributing to effective decision-making in classification tasks. ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in/s/store ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at support@campusx.in ⌚Time Stamps⌚ 00:00 - Intro 00:14 - Example 1 03:00 - Where is the Tree? 04:00 - Example 2 06:09 - What if we have numerical data? 07:57 - Geometric Intuition 10:50 - Pseudo Code 11:54 - Conclusion 14:00 - Terminology 14:53 - Unanswered Questions 16:16 - Advantages and Disadvantages 18:04 - CART 18:45 - Game Example 21:45 - How do decision trees work? / Entropy 22:15 - What is Entropy 25:40 - How to calculate Entropy 29:40 - Observations 31:35 - Entropy vs Probability 36:20 - Information Gain 41:40 - Gini Impurity 50:30 - Handling Numerical Data
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