VGG Network on cifar-100
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The basic model which is used everywhere and have many usecases in computer vision. Happy Reading 🙂
Published:
The basic model which is used everywhere and have many usecases in computer vision. Happy Reading 🙂
Published:
This is a starting of Deep learning and machine learning. Mainly talking basic model of CNN and results. Happy Experimenting 🙂
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If you want to know the basics of machine learning, this short read will clear most of the Why questions of machine learning.
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LSTMs are widely used architecture in NLP. In this blog i am trying to explain, what is architecture, how i trained model and what are the results. This model predicts most probable next word in a sentence.
Published:
The basic model which is used everywhere and have many usecases in computer vision. Happy Reading 🙂
Published:
This is a starting of Deep learning and machine learning. Mainly talking basic model of CNN and results. Happy Experimenting 🙂
Published:
This is a starting of Deep learning and machine learning. Mainly talking about Universal approximation theorem. Happy Reading 🙂
Published:
LSTMs are widely used architecture in NLP. In this blog i am trying to explain, what is architecture, how i trained model and what are the results. This model predicts most probable next word in a sentence.
Published:
LSTMs are widely used architecture in NLP. In this blog i am trying to explain, what is architecture, how i trained model and what are the results. This model predicts most probable next word in a sentence.
Published:
The basic model which is used everywhere and have many usecases in computer vision. Happy Reading 🙂
Published:
This is a starting of Deep learning and machine learning. Mainly talking basic model of CNN and results. Happy Experimenting 🙂
Published:
If you want to know the basics of machine learning, this short read will clear most of the Why questions of machine learning.
Published:
This is a starting of Deep learning and machine learning. Mainly talking about Universal approximation theorem. Happy Reading 🙂