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Deep learning-based vision is characterized by intricate frameworks thatoften necessitate a profound understanding, presenting a barrier to newcomersand limiting broad adoption. With many researchers grappling with theconstraints of smaller datasets, there's a pronounced reliance on pre-trainedneural networks, especially for tasks such as image classification. Thisreliance is further intensified in niche imaging areas where obtaining vastdatasets is challenging. Despite the widespread use of transfer learning as aremedy to the small dataset dilemma, a conspicuous absence of tailored auto-MLsolutions persists. Addressing these challenges is "Deep Fast Vision", a pythonlibrary that streamlines the deep learning process. This tool offers auser-friendly experience, enabling results through a simple nested dictionarydefinition, helping to democratize deep learning for non-experts. Designed forsimplicity and scalability, Deep Fast Vision appears as a bridge, connectingthe complexities of existing deep learning frameworks with the needs of adiverse user base.

Deep Fast Vision: A Python Library for Accelerated Deep Transfer Learning Vision Prototyping