Machine learning applications for the Internet of Things (IoT) pose unique challenges and necessitate understanding of large-scale multi-dimensional heterogeneous sensor data at varying granularities. We'll highlight the unique challenges posed by IoT applications especially for deep learning algorithms and we'll present some work on leveraging representation learning in conjunction with deep learning to design successful algorithms for these problems. We'll demonstrate the effectiveness of the proposed approaches on real-world IoT use cases. The proposed deep representation learning models are each trained using an NVIDIA Tesla M40 GPU. Finally, we'll discuss a technology view of deep learning in the context of IoT.