Abstract : The Image Caption Generator using Machine Learning employs advanced neural network architectures including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to automatically generate descriptive captions for images. Initially, the CNN extracts intricate visual features from the input image, encoding its content. The features are then passed to the RNN which generates sequential words, constructing coherent and contextually relevant captions. Through extensive training on large datasets of paired images and captions, the model refines its understanding of visual semantics and linguistic structures, enhancing its captioning accuracy. This technology has diverse applications, including assisting visually impaired individuals, enhancing content accessibility, and powering intelligent image search engines. It facilitates the creation of enriched multimedia content, aiding in social media sharing, news reporting, and website development. As machine learning algorithms progress, the Image Caption Generator promises even more nuanced and contextaware descriptions, bridging the gap between visual perception and linguistic expression.