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Name: Kasturi Chandra Shekhar This file guides you through to execute the files . File naming convention and Description K-Means Clustering.ipynb : This file contains the python implementation of the first two sections of Problem 1 i.e; Problem 1.1 and Problem1.2 which is K-means implementation with initial mu and sigma parameters K-Means Clustering 2.ipynb : This file contains the python implementation of the last section of Problem 1 i.e; Problem 1.3 K-means implementation with given mu and sigma values in problem 1.3 K-NN Classifier.ipynb : This file contains the python implementation of myknnclassify() K-NN regressor.ipynb : This file contains the python implementation of myknnregressor() K-NN Regressor.ipynb : This file contains the python implementation of myLWR() Report: This file consists of the entire summarization of the results acquired by the above python codes. Execution of the above files 1. You will need to install any latest version Python-3 2. You will need Anaconda to execute the above submitted python code.Anconda is required as it installs all the necessary packages for importing such as numpy,random...etc 3. After installing anaconda use -pip install notebook command to install jupyter notebook 4. Open jupyter notebook kernel by typing a command in the anaconda prompt $jupyter notebook -- command to open jupyter notebook 5. Open the files in jupyter notebook by selecting the open file option in the jupyter notebook 6. Run the files in individual kernels or files. or you can change the directory to the destination folder and enter jupyter notebook command to open the files in jupyter notebook
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Implemented various Machine Learning algorithms from scratch (k-means Clustering , k-nn classifier, k-nn regressor)
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