Identification of hadronic jets originating from heavy flavor quarks, particularly the beauty quark, is crucial for precision studies related to the top quark and Higgs boson, as well as for various searches for signatures of new physics beyond the Standard Model. The application of state-of-the-art machine learning algorithms adds a technical interest to this topic. Additionally, these concepts can be extended to other areas of physics. In this talk, I will provide a brief overview of various identification algorithms, discussing their performance in simulations and pp collision data across both boosted and resolved topologies. I will also explore potential future applications in astro-particle experiments, such as GRAPES-3.