Garbage is a waste substance abandoned by people generally, owing to a perceived lack of utility. Every day, a substantial amount of waste is generated that should be properly collected and categorized through a proper garbage management system. The first step after garbage collection is to separate or classify it into different categories like glass, paper, plastic, etc. to reuse, recycle, repair, and recover it. The existing classifiers can only classify the garbage into three or six categories. To address this, we have designed and implemented a Smarter Garbage Management System (GMS) using SVM and Convolutional Neural Network(CNN) that segregates garbage into eight classes and also labels the objects in the image namely cardboard, leather, glass, metal, plastic, paper, rubber and trash. Using transfer learning we have achieved up to 90.4% accuracy, which is higher than the existing classifiers.