Machine learning (ML) technology is being increasingly adopted across the embedded sector in applications ranging from consumer to industrial IoT. All because of its unique potential for innovation. With the combination of popular neural network frameworks such as Caffe and TensorFlow, embedded-optimized neural network software stack for Cortex-M processors, and high performance cores such as the Arm Cortex-M7 processor, exciting new possibilities are opened for ML applications at the end node. This means that a wide range of neural network applications, like image and audio recognition, can now be applied to Cortex-M based processors with optimized performance and energy efficiency.