Learning to create Machine Learning Algorithms

A Python implementation of k-means clustering algorithm

✍️ An intelligent system that takes a document and classifies different writing styles within the document using stylometric techniques.

Segmentation and Identification of Vertebrae in CT Scans using CNN, k-means Clustering and k-NN

โค้ดประกอบเนื้อหา Python Machine Learning เบื้องต้น

🍡 文本聚类 k-means算法及实战

• Proposed system enhances user experience by providing a recommendation in travel domain more specifically for food, hotel and travel places to provide user with various sets of options like time based, nearby places, rating based, user personalized suggestions, etc.M RECOMMENDATION METHODS : • Near-by Recommendation Algorithm - KNN Algorithm •…

A simple K-Means Clustering model implemented in python

zeta-lean: minimalistic python machine learning library built on top of numpy and matplotlib

Land surface classification using remote sensing data with unsupervised machine learning (k-means).

Comparison of Apriori and FP-Growth Algorithm in accuracy metrics, execution time and memory usage for a prediction system of dengue.

Content and Collaborative Filtering based book recommendation system

Centroid Neural Networks for Clustering

Clustering a set of word/tags using K-Means with word2vec or wordnet distance

The project groups scrapped News headlines using NLTK, K-Means clustering and Hierarchical clustering using Ward Method.

📊 数据挖掘常用算法：关联分析Apriori算法，数据分类决策树算法，数据聚类K-means算法

Build a machine learning model to detect change in Multi-temporal Satellite Images 🌍

Sequence clustering using k-means with dynamic time warping (DTW) and Damerau-Levenshtein distance as similarity measures

Implemented Content-based filtering, Collaborative filtering and K-Means Clustering on MovieLens Dataset(https://www.kaggle.com/rounakbanik/the-movies-dataset/data)

Color quantization is the process of reducing number of colors used in an image while trying to maintain the visual appearance of the original image.