Lesson 1 : Introduction to Machine Learning Lesson 2: How to Import & Pre Process DataLesson 3: Prediction using Linear RegressionLesson 4 : Logical Classification using Logistic Regression Lesson 5 : Object Classification using SVM Lesson 6 : Predictions using Naive Bayes Lesson 7 : Finding Nearest Neighbor using KNN Lesson 8 : Data Clustering using K means Lesson 9 : Random Forest ApplicationLesson 10 : Dimensionality Reduction AlgorithmLesson 11 : Regression using GBMLesson 12 : Data Analysis using XG BoostLesson 13 : Prediction using Light BGMLesson 14 : Prediction using CATBOOSTLesson 15 : Image Labelling Techniques Lesson 16 : NN Based Image Classification Lesson 17 : Image Classification – KNNLesson 18 : Image Classification – SVMLesson 19 : Project Demo – III Lesson 20 : Project Demo – IVĬATEGORY – III ARTIFICIAL INTELLIGENCE IN MATLAB Graphical User Interface – IILesson 6 : Commands, Control Statements & Loops in MATLABLesson 7 : Basic Image ManipulationLesson 8 : Image Blurring, De-Blurring & TransformationLesson 9 : Image Erosion, Dilution & FusionLesson 10 : De Noising in Images Lesson 11 : Filtering in ImagesLesson 12 : Image Compression – DWT & SWT Lesson 13 : Image Compression – SWT & Watermarking Lesson 14 : Feature Extraction in ImagesLesson 15 : GLCM Based Feature ExtractionLesson 16 : Image Segmentation – K Means Lesson 17 : Image Segmentation – APPLesson 18 : Image Segmentation – OTSU ThresholdingLesson 19 : Image Based Clustering Lesson 20 : Image Segmentation – Watershed Lesson 21 : Texture Based Segmentation using Gabor FilterLesson 22 : Edge Detection in ImagesLesson 23: Face Detection using HAAR CascadeLesson 24 : AES Based Image EncryptionLesson 25 : RSA Algorithm Based Image EncryptionLesson 26 : Image Pattern RecognitionLesson 27 : Training Image Datasets Lesson 28 : Neural Networks in Images Lesson 29 : Project Demo – I Lesson 30 : Project Demo – II Lesson 1 : Introduction to Image Processing & ApplicationsLesson 2 : MATLAB Fundamentals & Tool BoxLesson 3 : GUI, Graphs & Plots in MATLAB Lesson 4 : Graphical User Interface – I Lesson 5 : SYLLABUSWHY MATLABPRE REQUISITIESCERTIFICATION CATEGORY – I IMAGE PROCESSING USING MATLAB We promise you’ll get the BEST E LEARNING Experience you’ve ever had ! Program Overview ![]() Module IX : NLP & AI Implementation in MATLAB Module VIII : Deep Learning Implementation using MATLAB Module : VII : Regression & Data Analysis using MATLAB ![]() Module VI : Detection & Classification Applications Module V : Machine Learning Algorithms in MATLAB Module III : Algorithmic Approach in MATLAB Module II : Image Compression & Segmentation This Certified Course in MATLAB Programming provides the Learners with the Complete Assistance in Learning MATLAB Programming with ease.Ĭurriculum Designed suitably to enable Learners begin from Scratch ! ![]() Over 500+ Student Enrollments LEARN MATLAB PROGRAMMING at Your Ease Image Processing | Machine Learning | Artificial Intelligence using MATLAB Clarifications / Support 8925533489 Enhance your Skills in MATLAB Programming The Complete A- Z MATLAB Upskilling Program
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