The instability modes and non-linear behavior of a cavitating flow have been studied based on the experimental data obtained from planar Particle Image Velocimetry (PIV). Three data-driven techniques, Proper Orthogonal Decomposition (POD), Dynamic Mode Decomposition (DMD), and Clustered-based Reduced Order Modeling (CROM), are applied to the snapshots of the fluctuating component of velocity to investigate instability modes of the cavitating flow. DMD and POD analysis yield multiple modes are corresponding to slow-varying drift flow, cloud-shedding, and Kelvin-Helmholtz (KH) instability for a fixed inlet flow condition. The high coherence measure obtained from the instabilities suggests a transfer of energy from the largest scales, fluctuating mean flow, to the smaller scales such as cloud cavitation and Kelvin-Helmholtz (KH) instability. It is demonstrated that the POD decorrelation of length scales yields inherently quasi-periodic time dynamics, e.g., incommensurate frequencies. Moreover, the eigenvalue obtained from DMD revealed multiple harmonic with different decay rates associated with the cloud cavitation. The above-mentioned intermittent transition between distinct cloud shedding regimes is investigated via Clustered-based Reduced Order Modeling (CROM). Four aperiodic shedding regimes are identified. 68% of the time, triplets of vortices are formed, while 28% of the time, a pair of vortices are formed in the near wake of the throat. Dominant mechanisms governing the momentum transport and the turbulence kinetic energy production, destruction, and redistribution in distinct regions of the flow field have been identified using Gaussian Mixture Models (GMMs). The preceding data-driven techniques and in-depth analysis of the results facilitated modeling of the cavitation inception and break-up. Accordingly, a phase transition field model is developed using the ultra-fast Time-Resolved Particle Image Velocimetry (TR-PIV) and vapor void fraction spatial and temporal data. The data acquisition is implemented in a Venturi-type test section. The approximate Reynolds number based upon the throat height is 10,000, and the approximate cavitation number is 1.95. The non-equilibrium cavitation model assumes that the phase production and destruction are correlated to the static pressure field, pressure spatial derivatives, void fraction, and divergence of the velocity field. Finally, the dependence of the model on the empirical constants has been investigated. / Doctor of Philosophy / A cavitation bubble occurs where the pressure field is below the saturation pressure of the liquid. Accumulation of the cavitation bubble forms a cavitating flow. This phenomenon is observed in pumps, propulsion systems, internal combustion engines, and rocket engines. Identifying the mechanisms leading to cavitation-induced damages is imperative in the design of the devices. In this regard, investigation of the cavitation bubble inception, deformation, collapse, and intermittent regime change is mandatory in learning the primary mechanisms of the stresses imposed on the device. Experiments and high-fidelity numerical and analytical methods can be employed to shed light on flow physics. The current study adopted joint experimental methods, data analysis techniques, and computational approaches to scrutinize the unsteady cavitating flow underlying physics as it occurs past the throat of a Venturi-type profile. Different mechanisms of instabilities are identified by applying the data-driven techniques to the raw images of the cavitating flow. The path of the transitions between physically different instabilities mechanisms is examined. The local dominant balance between stress terms in the conservation of momentum equation is identified, and the stress terms roles in cavitating flow instabilities and advective acceleration are determined. A new cavitation model is developed and validated against the experimental results. The new model improves the prediction of the void fraction in different regions of the flow field, making it feasible to simulate different regimes of cavitating flow. Finally, the dominant mechanism governing the liquid-vapor transition and the transport of the void fraction is described.