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MNIST_WITHOUT_SKLEARN: The MNIST_Scipy.py module is presented which, using the Scipy library, is applied to the recognition of handwritten characters contained in the MNIST file, achieving a similar hit rate than the module referenced at https://github.com/ablanco1950 / MNIST_KNN Although with a longer execution time.
Product Recommendation Engine Recommendation engines are now a one of the most common Machine Learning project that can be seen now-a-days. In fact, some biggest brands are build around one, like Netflix, Amazon, Google, etc. Thirty-five percent of purchases on Amazon come from product recommendations.
Cluster your data using the euclidean distance and watch the distance matrix for each epoch of the algorithm. The program reads the data by a .csv file and plots the results on dendrogram and radar plots.
Java Program Designed to recognise a digit from a 8*8 grid of numbers, Categorisation Task, Completed using 2 Solutions. Euclidean Distance and Self Organising Maps.
An academic project to find the most similar image to the given input image, based on Image Processing, Cosine Similarity Model, StreamLit, written primarily in Python using Visual Studio Code and Jupyter Notebook
In this repo i have tried to explain how to calculate Euclidean Distance,manhattan distance, and Finally Calculating the Dissimilarity Matrix/Distance Matrix using python.
Implementation (VHDL) and verification of the accelerator proposed in the paper "Hardware Accelerator for Shapelet Distance Computation in Time-Series Classification", from May 2020