The article explores common data clustering techniques, with a focus on spectral clustering. Using k-means to compute cluster labels from eigenvectors is found to be the best approach, despite variations and complexities.
Getir, the ultrafast grocery delivery pioneer, has implemented an end-to-end workforce management system using Amazon Forecast and AWS Step Functions, resulting in a 70% reduction in modelling time and a 90% improvement in prediction accuracy. This comprehensive project calculates courier requirements and solves the shift assignment problem, optimizing shift schedules and minimizing missed orders.
Mistral AI announces Mixtral 8x7B, an AI language model that matches OpenAI's GPT-3.5 in performance, bringing us closer to having a ChatGPT-3.5-level AI assistant that can run locally. Mistral's models have open weights and fewer restrictions than those from OpenAI, Anthropic, or Google.
Spectral clustering is a complex machine learning technique that uncovers patterns in data. Implementing it involves computing affinity and Laplacian matrices, eigenvector embeddings, and performing k-means clustering.