Huawei HCIA AI H13-311: Real-Life Machine Learning with Linear Regression

📌 Huawei HCIA AI H13-311 | Real-Life Machine Learning Case Study – Predicting House Prices with Linear Regression

Welcome back! In this final section of Chapter 2, we take everything we’ve learned so far—definitions, classifications, popular algorithms, and essential ML methods—and bring it all together in a real-world case study. 🎯

This time, we’re working with a classic housing price dataset containing over 21,613 entries. Each record includes the living area (square footage) and the residential price—a perfect scenario to explore regression tasks in machine learning.

🧠 What You’ll Learn in This Video:
🔹 How to identify the problem type: Regression vs Classification
🔹 Why this problem is a regression task (continuous value prediction)
🔹 How to use Linear Regression with one-dimensional input
🔹 What a linear regression function looks like and how to construct it
🔹 The importance of loss function and how it’s calculated
🔹 How gradient descent algorithm helps find optimal model parameters
🔹 The step-by-step iteration process from random start to model convergence
🔹 How to avoid overfitting using L1 (Lasso) and L2 (Ridge) regularization
🔹 When to switch to complex models like GBDT for underfitting problems
🔹 Final thoughts on improving models through data cleaning & feature engineering

🔍 ML in Practice – From Dataset to Deployment:
This case study isn’t just about coding—it’s about thinking like a data scientist. You’ll walk through each essential phase:

📥 Data Collection

🧹 Data Cleaning

🧬 Feature Extraction

🤖 Model Training

✅ Model Evaluation

🚀 Model Deployment

We’ll show how a simple input (house area) can train a model capable of accurately predicting housing prices using a linear function. The magic lies in understanding how to minimize errors and find that one perfect line through gradient descent.

🧩 Bonus Concepts Covered:
🧠 Difference between Supervised and Unsupervised Learning

⚠️ Why Gradient Descent is popular, but not the only optimization method

💻 Best practices to build and tune real-world ML models

🔍 Where to explore more on Huawei Learning & Huawei Support Case Library

🎓 Whether you’re preparing for the Huawei HCIA AI H13-311 certification, or just want to build a solid foundation in machine learning, this chapter is packed with valuable insights and practical knowledge. Get ready to take your understanding of ML to the next level!

💬 If you enjoyed the video, don’t forget to like, comment, and subscribe for more AI & ML tutorials. And let us know—what real-world problems would you like us to solve next using machine learning?

#HuaweiHCIA #H13_311 #MachineLearning #LinearRegression #RegressionTask #GradientDescent #L1Regularization #L2Regularization #MLCaseStudy #HousingDataset #AIforBeginners #MLProject #RealWorldML #HCIAAI #DataScience #ModelTraining #ModelEvaluation #MLWorkflow





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