| Sumario: | Classification of the modulation techniques of the signal at the receiver's end is one of the imporatant key features in this world with advanced technologies. This classification of modulation techniques is also one of the key applications for military purposes and during the time of war. The new progressions in the field of Machine Learning and Deep learning have flooded the interest of the scientist in the area of wireless communications which made the development of Automatic Modulation Classification(AMC) easy. So in this work, we develop an automatic modulation classification using neural networks and also we use other regular methods like the Likelihood approach and predict the accuracy of the developed model. We consider datasets and divide the datasets for training and testing, the data is considered as 80% for training and the remaining 20% for testing. We finish up by comparing all the results we obtain with the developed models and propose future work for additional exploration and developments in the area of wireless communications.
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