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80. Sampling Techniques in Machine Learning: Methods and Applications 📊🔍

Explore the essential sampling techniques used in machine learning to manage data effectively and improve model performance. 🌟 Learn about various methods such as Random Sampling, Stratified Sampling etc. 💡 Understand how these techniques help in handling imbalanced datasets, reducing computation costs, and ensuring representative samples for training and evaluation. 📈 This video covers practical examples, use cases, and the impact of different sampling strategies on your machine learning projects. Whether you're looking to enhance data quality or optimize model training, this guide provides valuable insights into effective sampling methods. Let’s dive into the world of sampling techniques and refine your data management skills! 🚀📉 🔗 Link to Repo: https://github.com/codehax41/Machine-... ------------------------------------------------------------------------------------------------------------- 🎬 All Playlist in my channel: 🤖 Machine Learning Playlist:    • Machine Learning Beginner to Expert || End...   ⚙️ ML Ops Playlist:    • MLOps Tutorial with Project Step by Step   🧠 Deep Learning Playlist:    • Плейлист   🎓 Reinforcement Learning Playlist:    • Reinforcement Learning using Python   📈 Stats & Probability Playlist:    • Statistics & Probability for Data Scince   --------------------------------------------------------------------------------------------------------------- 🌐 Connect with me here: 👨‍💻 Github: https://github.com/codehax41 📘 Facebook:   / ramsundar.12380   📷 Instagram:   / mee_iamram   --------------------------------------------------------------------------------------------------------------- 🙏 THANKS & Love you all!!! ❤️ --------------------------------------------------------------------------------------------------------------- #MachineLearning, #AI, #DataScience, #LLM, #GenAI, #ChatGPT #Gemini 🚀 ---------------------------------------------------------------------------------------------------------------