🧩 Part 8/8

✔ What is Model Deployment and Integration?
✔ Why Use Matlab for Machine Learning Model Deployment and Integration?
✔ How to Deploy and Integrate Machine Learning Models Using Matlab
✔ MATLAB Compiler
✔ MATLAB Production Server
✔ MATLAB Coder
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🧩 Part 7/8

✔ What is Model Optimization and Validation?
✔ Model Optimization
✔ Model Validation
✔ How to Optimize and Validate Machine Learning Models in Matlab?
✔ Cross-Validation
✔ Grid Search
✔ Performance Metrics
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🧩 Part 6/8

✔ What is Deep Learning and Why Use Matlab?
✔ Neural Networks in Matlab
✔ Creating and Training a Neural Network
✔ Evaluating and Testing a Neural Network
✔ Convolutional Neural Networks in Matlab
✔ Creating and Training a Convolutional Neural Network
✔ Evaluating and Testing a Convolutional Neural Network
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🧩 Part 5/8

✔ What is Unsupervised Learning?
✔ Types of Unsupervised Learning
✔ Applications of Unsupervised Learning
✔ How to Perform Unsupervised Learning in Matlab
✔ Data Preparation and Visualization
✔ Clustering Algorithms
✔ Dimensionality Reduction Algorithms
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🧩 Part 4/8

✔ Matlab Basics for Machine Learning
✔ Data Import and Preprocessing
✔ Visualization and Exploration
✔ Regression Models
✔ Linear Regression
✔ Nonlinear Regression
✔ Regularization and Validation
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🧩 Part 3/8

✔ What are Features and Why are They Important?
✔ Feature Extraction Methods in Matlab
✔ Principal Component Analysis (PCA)
✔ Linear Discriminant Analysis (LDA)
✔ Independent Component Analysis (ICA)
✔ Feature Selection Methods in Matlab
✔ Filter Methods
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🧩 Part 2/8

✔ Data Import and Exploration
✔ Importing Data from Different Sources
✔ Exploring Data with Statistics and Plots
✔ Data Cleaning and Transformation
✔ Handling Missing Values and Outliers
✔ Scaling, Normalizing, and Encoding Data
✔ Data Visualization and Analysis
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🧩 Part 1/8

✔ What is Matlab and Why Use it for Machine Learning?
✔ How to Install and Set Up Matlab on Your Computer
✔ How to Use Matlab for Data Preprocessing and Visualization
✔ How to Use Matlab for Supervised Learning Algorithms
✔ Linear Regression
✔ Logistic Regression
✔ Support Vector Machines
✔ Decision Trees and Random Forests
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