Why this course?

Description

                                      

                                  Matlab Basics in Telugu

 

Description:

"Matlab Programming for Beginners" is a beginner-friendly guide and learning resource  

Designed to introduce individuals to the MATLAB programming language. MATLAB, short for "Matrix Laboratory," is a high-level programming environment commonly used in various fields such as engineering, science, mathematics, and data analysis. This resource aims to provide an accessible and structured approach for newcomers to learn the fundamentals of MATLAB programming.

Uses of MATLAB:

 

Beginners can use MATLAB for basic signal processing tasks like filtering, Fourier analysis, and image processing.

 

MATLAB's built-in functions and toolboxes simplify the implementation of algorithms in these domains.

 

MATLAB is commonly used in research for prototyping and validating ideas before implementing them in more complex environments.

 

MATLAB has an active user community and extensive learning resources.

 

Beginners can benefit from online forums, tutorials, and documentation to enhance their programming skills.

 

Matlab Basics:

Graphical user interface:

A Graphical User Interface (GUI) is a visual interface that allows users to interact with a computer or software application using graphical elements such as icons, buttons, and windows. GUIs are designed to enhance user experience by providing an intuitive and visually appealing way to interact with complex systems.

Computer vision:

MATLAB's Computer Vision Toolbox offers functionalities for image analysis, object detection, feature extraction, and more.

 

NEURO -FUZZY DESIGNER MATLAB: Neuro-fuzzy design using MATLAB. Nero-fuzzy systems combine the adaptive learning capabilities of neural networks with the inguistic representation of fuzzy logic to create intelligent systems capable of handling complex and uncertain information.

 

NEURAL NETWORK using MATLAB:

Neural network using MATLAB involves defining the network architecture, preparing data, training the network, and evaluating its performance.

 

DEEP LEARNING FOR SPEECH SIGNAL USING MATLAB (LSTM/CNN):

Deep learning for speech signals involves leveraging advanced neural network architectures such as Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) to analyse and process audio data.

FACE RECOGNITION USING MATLAB:

Face recognition in MATLAB involves utilizing computer vision and machine learning techniques to detect and recognize faces in images or video

AUGMENTED REALITY MATLAB:

Augmented Reality (AR) refers to the technology that overlays digital information, such as images, text, or 3D models, onto the real-world environment in real-time

 

ARDUINO PROGRAMMING MATLAB:

Programming Arduino using MATLAB involves interfacing MATLAB with an Arduino board to control and monitor hardware.

Connect your Arduino board to your computer using a USB cable.

 

 

RCNN USING MATLAB:

Region-based Convolutional Neural Network (R-CNN) is a powerful object detection framework, and MATLAB's Computer Vision Toolbox and Deep Learning Toolbox provide a convenient environment for its implementation. Organize a labelled dataset containing images with annotated objects.

 

MACHINE LEARNING AND LOT USING MATLAB:

MATLAB for machine learning involves leveraging its various toolboxes and functionalities to develop, train, and deploy machine learning models. MATLAB provides an extensive set of tools for tasks such as data pre-processing, feature engineering, model training, and performance evaluation.

 

SLAM USING MATLAB:

Simultaneous Localization and Mapping (SLAM) is a technique used in robotics and computer vision to enable a device, such as a robot or a vehicle, to map its environment and simultaneously determine its own position within that environment.

MODULES OF Matlab Basics in Telugu:

 

MODULE: 1.) Getting Started With USING MATLAB

 

MODULE: 2.) image processing USING MATLAB

 

MODULE: 3.) VIDEO PROCESSING USING MATLAB

 

MODULE: 4) GRAPHICAL USER INTERFACE USING MATLAB

 

MODULE: 5.) APP DEVELOPEMENT USING MATLAB

 

MODULE: 6.) COMPUTER VISION USING MATLAB

 

MODULE: 7.) FUZZY LOGIC DESIGN USING MATLAB

 

MODULE: 8.) NEURO -FUZZY DESIGNER USING MATLAB

 

MODULE: 9.) NEURAL NETWORK USING MATLAB

 

MODULE: 10.) FEAUTRES EXTRACTION USING MATLAB

 

MODULE: 13.) DEEP LEARNING FOR SPEECH SIGNAL USING MATLAB

(LSTM/CNN)

MODULE: 14.) IMAGE SEGMENTATION USING MATLAB

 

MODULE: 15.) IMAGE COMPRESSION USING MATLAB

 

MODULE: 16.) FACE RECOGNITION MATLAB USING MATLAB

 

MODULE: 17.) AUGMENTED REALITY USING MATLAB

 

MODULE: 18.)  IMAGE DENOISING USING MATLAB

 

MODULE: 19.) ARDUINO PROGRAMMING USING MATLAB

 

MODULE: 20.) RCNN USING MATLAB

 

MODULE: 21.) STEGANOGRAPHY USING MATLAB

 

MODULE: 22.)  REAL-TIME OBJECT DETECTION USING MATLAB

 

MODULE: 23.) RASPBERRY PI PROGRAMMING USING MATLAB

 

MODULE: 24.) SPEECH PROCESSING USING MATLAB

 

MODULE: 25.) AUDIO PROCESSING USING MATLAB

 

MODULE: 26.)JETSON NANO PROGRAMMING USING MATLAB

 

MODULE: 27.) CRYPTOGRAPHY USING MATLAB

 

MODULE: 28.)MACHINE LEARNING AND LOT USING MATLAB

 

MODULE: 29.)SLAM USING MATLAB

 

MODULE: 30.)SEMANTIC SEGMENTATION USING DEEP LEARNING USING MATLAB               

 

 

 

.