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Welcome to the Breast-Cancer-Histology-Image-Classification wiki!

Monthly Progress

Month 1 (July 2018)

• Explore the Machine Learning

• Developed a deep knowledge of Supervised Machine Learning

Month 2 (August 2018)

• Explored MP Model of Neuron, Perceptron Model and Adaline Model

• Developed a traditional ANN for Image classfication

Month 3 (September 2018)

• Understand the need of CNN

• Designed a basic 3 Layers CNN for Image classification

Month 4 (October 2018)

• Trained the Developed model with our data set

• Explore the over fitting problem

Month 5 (November 2018)

• Explore the LeNet Architecture

• Designed a LeNet Architecture to improve the performance

Month 6 (December 2018)

• Explore the AlexNet Architecture

• Designed a AlexNet Architecture to improve the performance

Month 7 (January 2019)

• Understand the need of Large Data set

• Perform the Data Augmentation to increase the Data size

Month 8 (February 2019)

• Explore the Residural Network (52 layers) Architecture

• Designed a Residual Networks Architecture to improve the performance

Month 9 (March 2019)

• Explore the DenseNet Architecture

• Designed a DenseNet Architecture to improve the performance

Month 10 (Apr 2019)

• Train and Test the model in Google Cloud

• Prepare the Project Report and Presentation