We explore the possibility of using Machine Learning techniques for Weakly Interacting Massive Particle (WIMP) Dark Matter at LHC and at Xenon1T experiment. We suggest using deep and Convolutional Neural Networks for the data processed in the form of images of Time Projection Chamber in the Xenon experiment and higher dimensional histograms of the kinematic variables for the collider DM searches.