Vader stands for Valence Aware Dictionary and sEntiment Reasoner. It is a lexicon and rule based tool for sentiment analysis. It is specifically attuned to sentiments expressed in social media. It is used for analyzing the sentiment of text which contains both positive and negative polarity. The main function of VADER is to quantify how much of positive or negative emotion is present in the text. It can also measure the intensity of emotion.

To build a machine learning model dataset is one of the main parts. Before we start with any algorithm we need to have a proper understanding of the data. These machine learning datasets are basically used for research purposes. Most of the datasets are homogeneous in nature. We use a dataset to train and evaluate our model and it plays a very vital role in the whole process. If our dataset is structured, less noisy, and properly cleaned then our model will give good accuracy on the evaluation time. Imagenet dataset is made by the group of researchers and the images in the dataset organized according to the WordNet hierarchy. This dataset can be used for machine learning purposes and computer vision research fields as well.