A data-driven machine learning processor (D2MLP) with MIMD architecture is designed for big data analysis. Adopting the configurable counting engine array with 3-layer dimension merging, the D2MLP processes maximal 1-128/1024 dimensional data with parallel 64/8 queries in learning stage. Implement in 90nm CMOS technology, the D2MLP achieves 219.9x and 8.2x faster processing time than CPU and GPGPU, respectively. In application phase, maximal 22.7k 128-class classifications/s are performed with the learned density model. Operated at 1.0V and 165MHz, the D2MLP demonstrates an energy-efficient solution for learning and classification with 7.11mJ/Gb/query and 2.3μJ/classification, respectively.