Content:

• AutoEncoder: This project is to impliment denoising autoencoder(convolution architechture)
• Back Propagation: This project is to impliment backpropagation algorithm from scratch(Using only numpy)
• Decision Tree: This project contains the detailed implication(from scratch) of the decision tree algorithm.
• Kaggle competition: This project contains the ongoing coding(unpolished) and examples(of peers) for Kaggle.
• Linear Regression: This project contains the implementation of linear regression algorithm from scratch.
• Material Search Engine: This project contains the detail implementation of random forest algorithm for material search engine
• Naive Bayes: This project contains the detail implementation of Naive Bayes algorithm from scratch.
• Random Forest: This project contains the detail implementation of Random forest algorithm from scratch.
• TensorFlow codes: This project contains the various TensorFlow codes. This project focused on implementation of the various machine learning algorithms and deep learning algorithms in TensorFlow.
• Python codes: This project is for the python tutorials for beginners.

© Mohendra Roy