Hey, let's play a simple game. We will flash a few animal images. Can you try to identify them? Black-built cocoon, great-crested flycatcher, blue-grove speak, dark-eyed junko, belted kingfisher, suited Oreo, white pelican. How many did you get it right? What? Zero. Monitoring bird diversity has been an important task from an ecological and environmental point of view. By monitoring birds in habitats, we can identify the species, sites and possible threats, assessing progress in efforts to conserve biodiversity and evaluating whether policies and actions are having any impact. While bird monitoring is a well-established process, it is not very scalable, because it is time-consuming and largely carried out manually. Besides, it also requires a huge amount of professional skills to identify bird species, making qualified manpower hard to train. There are any better, more efficient methods for bird monitoring. Yes, how about using neural network to analyze and classify bird images collected from monitors? Neural network is a machine learning method inspired by biological neurons. It consists of layers of algorithms that stack together, like how neurons are connected, to recognize underlying relationships in a set of data. To differentiate between bird species that are hard to distinguish, we focus on the fine grained classification that is especially good on identifying objects that are visually similar by extracting details. We train our model using KELTEK UCSD birds data set with 200 bird species containing more than 10,000 images. We adopted transfer learning with ResNet 152 and investigators the impact of image augmentation and various hyperparameters, such as the optimizer and the amount of frozen weights on the accuracy of the model. With modifications on existing ResNet model, we have managed to improve the accuracy from 81.5% to 82.9% and reduce the training time by 1.3% approximately. Now the model can identify birds of different species at a really high success rate. It can possibly save a huge amount of time and manpower and contribute to bird monitoring and biodiversity conservation.