What are the real world applications of machine learning?

Описание: Welcome to this complete Machine Learning Course Series specially designed for III Year Engineering Students (ECE / CSE) and beginners in AI & ML.
In this playlist, you will learn Machine Learning step-by-step from fundamentals to advanced concepts based strictly on university syllabus:
📌 UNIT-1: Introduction to Machine Learning • What is Machine Learning
• Traditional vs ML approach
• Types of ML (Supervised, Unsupervised, Reinforcement)
• Data Types & ML Workflow
• Applications of ML
• Python tools: NumPy, Pandas, Scikit-learn, Matplotlib
📌 UNIT-2: Exploratory Data Analysis (EDA) • Data Cleaning & Preprocessing
• Missing values, Outliers
• Feature Scaling & Transformation
• PCA
• Feature Engineering
• One-Hot Encoding
• Automatic Feature Selection
📌 UNIT-3: Supervised Learning • Classification vs Regression
• KNN, Logistic Regression, Naive Bayes
• Decision Trees, Random Forest
• AdaBoost, Gradient Boosting
• Support Vector Machine (SVM)
• Linear, Ridge, Lasso & Polynomial Regression
📌 UNIT-4: Unsupervised Learning • Clustering Concepts
• K-Means
• Hierarchical Clustering
• DBSCAN
• Hard vs Soft Clustering
📌 UNIT-5: Model Evaluation & Visualization • Confusion Matrix
• Accuracy, Precision, Recall, F1-Score
• ROC Curve
• MSE, RMSE, MAE, R²
• Cross Validation
• Grid Search
• Data Visualization (Histogram, Boxplot, Heatmap, Scatter Plot)
🎯 Perfect for: ✔ Semester exams
✔ Interview preparation
✔ Beginners in ML
✔ Final year projects
✔ Research scholars
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