Machine Learning Project-Predicting Manufacturing Defects: A Data-Driven Approach to Quality Control
In this video, we showcase how Machine Learning enhances quality control in manufacturing by predicting defects with high accuracy! ✅
🔹 Built a Random Forest model achieving 96.45% accuracy for defect prediction.
🔹 Compared multiple ML models (Logistic Regression, Decision Tree, KNN, Naïve Bayes, Neural Networks) to determine the best approach.
🔹 Implemented data preprocessing & feature engineering to optimise performance.
🔹 Automated defect detection & improved energy efficiency with AI-driven solutions.
#MachineLearning #AI #QualityControl #Manufacturing #DataScience
In this video, we showcase how Machine Learning enhances quality control in manufacturing by predicting defects with high accuracy! ✅
🔹 Built a Random Forest model achieving 96.45% accuracy for defect prediction.
🔹 Compared multiple ML models (Logistic Regression, Decision Tree, KNN, Naïve Bayes, Neural Networks) to determine the best approach.
🔹 Implemented data preprocessing & feature engineering to optimise performance.
🔹 Automated defect detection & improved energy efficiency with AI-driven solutions.
#MachineLearning #AI #QualityControl #Manufacturing #DataScience
