Course: Digit Recognizer in MATLAB using MNIST Dataset

Digit Recognizer in MATLAB using MNIST Dataset

  • Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App
  • Self-Paced
About this Course

Hand Written Character Recognition have always been a tricky task for machines, as well as humans. Designing a Machine Learning Model to automatically detect hand written characters is challenging as well as exciting technique. This Course will guide you through the process of understanding MNIST dataset, which is a benchmark dataset for hand written characters, and training a machine learning model on that dataset for designing a digit recognizer of your own.

Who this course is for:

  • Anyone interested in designing Neural Network in MATLAB
  • Anyone who wants to learn about working on MNIST Dataset
  • Anyone interested in starting Machine Learning
Basic knowledge
  • Basic Knowledge of MATLAB can be helpful and a basic understanding of Machine Learning and Neural Networks is must. Refer to my previous course for that
What you will learn
  • A clear understanding of MNIST Dataset and how it is helpful in Hand written character Recognition. Training a complex model on the dataset in simple steps. Analysis of the model and using it for further predictions
Number of Lectures: 6
Total Duration: 00:52:26
  • Introduction  
MNIST Dataset
  • What is MNIST Dataset?  

    A brief description of MNIST Dataset.

Data Pre Processing
  • Data Download and Import in MATLAB  

    Downloading the MNIST Dataset from reliable source and importing it in Matlab.

  • Pre Processing in MATLAB  

    Using MATLAB scripts to process the data into suitable form.

Training and Testing
  • Training the Model  

    Selecting important hyperparameters and training the model.

  • Analyzing and testing the trained Model  

    Quick Analysis of the Model and testing the model on new data to see how it predicts.

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