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)
This is a comprehensive guide to understanding Gradient Descent. We'll cover the entire process from scratch, providing an end-to-end view. Plus, witness a visual representation with a Gradient Descent animation. Code used: https://github.com/campusx-official/100-days-of-machine-learning/tree/main/day51-gradient-descent Google Tool used: https://developers.google.com/machine-learning/crash-course/fitter/graph ============================ 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 01:15 - Summary of Gradient Descent 04:10 - What is gradient descent? 05:22 - Plan of attack 07:25 - Intuition for GD 28:45 - Mathematical Formulation of Gradient Descent 36:11 - Code Demo 47:41 - Creating our own class and methods 57:16 - Vizualizing our class 01:05:05 - Effect of Learning Rate 01:07:33 - Universality of GD 01:10:23 - Performing Gradient Descent by adding 'm' 01:14:15 - Vizualisation 01:23:48 - Code Demo and Vizualization 01:44:35 - Effect of Learning rate 01:49:25 - Effects of Loss Function 01:55:12 - Effect of Data
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