Abstract: For the last 10 years, we have seen a rapid adoption of deep learning techniques across many disciplines, ranging from self-driving vehicles, credit card rating to biomedicine. Along with this wave, we have seen rapid adoption and rejection in the nascent field of Machine Learning and Sciences. While we see more and more people working in the area of Machine Learning and Sciences, there are also quite a number of skeptics (sometimes for very good reasons). Some of us are believers of using deep learning as a last resort, and I will showcase a few of these scientific challenges ranging from understanding our Universe, the Milky Way, the Solar System to our genome.