Image Classification Tutorial-1.1(MNIST Hand Written digit datasets using Neural Networks)
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This video of Automation Anomaly is bsed on "Image Classification", which will provide you with a comprehensive and detailed knowledge of Image classification and how it can be implemented using Keras library. Also,this video will help you to understand the basic concept of Image classifier to build your own Image Classifier from scratch.
I hope you guys like my introductory video on Image Classification Tutorial series.
Firstly, we will write code to upload the MNIST datasets from keras and we will plot MNIST hand written digit by using python's matplotlib library. Then we will see the use of python's assert statement for debugging to test some conditions. Moreover, we are going to check and understand the size and shape of our training and testing datasets. Lastly, we will see how our datasets is distributed over 10 different classes of hand written digit datasets.
In my next video we will see the concept of architecture of Neural Network and also we are going to train a neural network to identify MNIST hand written digit datasets. In addition, I will give brief explanation on one hot encoding for data labeling, relu and softmax activation function. So get ready for our next and very exciting video of image classification: Tutorial 1.2.
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