Ever since its discovery back in 1964 Cosmic Microwave Background (CMB) has been of great interest to cosmologists and played a crucial role in understanding and studying the early universe .One of the most interesting topic of current interest is dark matter and its existence is by now well established. By analyzing the CMB data we can estimate the dark matter density of the universe.With vast amount of astronomical data already present and a more vast amount which is to come in future,

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... Learning techniques can provide a variety of benefits in astrophysical and cosomological research. Here I explore the use of deep learning to estimate dark matter density. I have used convolutional neural networks in this paper. I have used simulated CMB temprature maps as a dataset to train the neural networks and correlate the dark matter density from the power spectrum of the corrseponding simlutaed CMB temprature map.