This academic paper, published in the Indonesian Journal of Electrical Engineering and Computer Science, reviews the potential applications of deep learning (DL) in transforming the economy of Pakistan. The authors argue that DL can play a vital role in analyzing large datasets to gain valuable insights into economic patterns and trends. They explore a wide range of DL models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and transformers, highlighting their potential applications in areas such as finance, agriculture, and social protection. The paper also discusses the challenges of implementing DL in Pakistan, such as data availability and computational resources, and proposes solutions to these challenges. Ultimately, the authors emphasize the importance of targeted research and ethical considerations in maximizing DL's impact on economic insights and innovation.

Deep learning for economic transformation: a parametric review

Deep Learning For Economic Transformation of Pakistan

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