- How are pre-trained word vectors obtained?
From an existing database such as GLOVE or word2vec - How do we map from an image feature embedding to word embedding in Zero-shot learning?
By creating a suitable neural network that returns a vector of the same shape as word-embedding and training with mse-loss (comparing prediction with actual word-embedding) - Why is the Siamese network called so?
Because we always produce and compare two outputs with each other, for identicalness. Siamese stands for twins. - How does the Siamese network come up with the similarity between the two images?
The loss function forces the network to predict that the outputs have a smaller distance if the images are similar.
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V Kishore Ayyadevara leads a team focused on using AI to solve problems in the healthcare space. He has 10 years' experience in data science, solving problems to improve customer experience in leading technology companies. In his current role, he is responsible for developing a variety of cutting edge analytical solutions that have an impact at scale while building strong technical teams. Prior to this, Kishore authored three books — Pro Machine Learning Algorithms, Hands-on Machine Learning with Google Cloud Platform, and SciPy Recipes. Kishore is an active learner with keen interest in identifying problems that can be solved using data, simplifying the complexity and in transferring techniques across domains to achieve quantifiable results.
Read more about V Kishore Ayyadevara
Yeshwanth is a highly accomplished data scientist manager with 9+ years of experience in deep learning and document analysis. He has made significant contributions to the field, including building software for end-to-end document digitization, resulting in substantial cost savings. Yeshwanth's expertise extends to developing modules in OCR, word detection, and synthetic document generation. His groundbreaking work has been recognized through multiple patents. He also created a few Python libraries. With a passion for disrupting unsupervised and self-supervised learning, Yeshwanth is dedicated to reducing reliance on manual annotation and driving innovative solutions in the field of data science.
Read more about Yeshwanth Reddy
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V Kishore Ayyadevara leads a team focused on using AI to solve problems in the healthcare space. He has 10 years' experience in data science, solving problems to improve customer experience in leading technology companies. In his current role, he is responsible for developing a variety of cutting edge analytical solutions that have an impact at scale while building strong technical teams. Prior to this, Kishore authored three books — Pro Machine Learning Algorithms, Hands-on Machine Learning with Google Cloud Platform, and SciPy Recipes. Kishore is an active learner with keen interest in identifying problems that can be solved using data, simplifying the complexity and in transferring techniques across domains to achieve quantifiable results.
Read more about V Kishore Ayyadevara
Yeshwanth is a highly accomplished data scientist manager with 9+ years of experience in deep learning and document analysis. He has made significant contributions to the field, including building software for end-to-end document digitization, resulting in substantial cost savings. Yeshwanth's expertise extends to developing modules in OCR, word detection, and synthetic document generation. His groundbreaking work has been recognized through multiple patents. He also created a few Python libraries. With a passion for disrupting unsupervised and self-supervised learning, Yeshwanth is dedicated to reducing reliance on manual annotation and driving innovative solutions in the field of data science.
Read more about Yeshwanth Reddy