DataHour: Contrastive Learning for Image Classification
DataHour: Contrastive Learning for Image Classification
10 Mar 202313:03pm - 10 Mar 202314:03pm
DataHour: Contrastive Learning for Image Classification
About the Event
Contrastive Learning is a type of unsupervised learning in machine learning where the goal is to learn useful representations of data by contrasting different views of the same data. The basic idea is to train a model to recognize similarities and differences between pairs of data points, where each pair consists of a "positive" example (e.g., two different views of the same image) and a "negative" example (e.g., two different images).
The model is trained to maximize the similarity between the positive examples and minimize the similarity between the negative examples. By doing this, the model learns to capture the important features of the data that are common across different views and that are distinctive between different data points. These learned representations can then be used for a variety of downstream tasks, such as image classification, object detection, and natural language processing. Contrastive learning has recently shown promising results in various applications, and is an active area of research in the machine learning community.
In this DataHour, Ashok will explain how Contrastive Learning is used for performing image classification,
Prerequisites: Basic understanding of Machine learning, Computer Vision and Deep Learning (TensorFlow) and interest in learning Data Science and Machine Learning.
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- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
Who is this DataHour for?
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
About the Speaker
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