who can implement classifiers from scratch

You will implement K-Nearest-Neighbor (kNN), Centroidbased Rocchio, Naive Bayes (NB) and Support Vector Machine (SVM) classifiers from scratch (that is, without using scikit-learn APIs) in Python. You will use a subset of the 20 Newsgroups dataset. The full data set contains 20,000 newsgroup documents, partitioned (nearly) evenly across 20 different newsgroups and has been used for experiments in text applications of machine learning techniques, such as text classification and text clustering. This assignment dataset contains a pre-processed subset of 1000 documents and a vocabulary (dictionary) of 5,500 terms.