Unlike English, Grammar checker is a vital problem for many languages in India. The Grammar corrector (GC) based on the syntactic and semantic information of a Nepali sentence is modelled. Skip-gram model is used for the word to vector encoding. Window size of 3 context words is employed for the word to vector encoding. The network is trained up to the negative log entropy goes to 0.05. The network is tested over 500 incorrect syntactics and semantics of Nepali sentences. The network has suggested the corrections with the accuracy of 96.4%.