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Mar 10, 2025 · 6 min read · Transformer is a deep neural network architecture that introduced in “attention is all you need”. It is designed for sequence to sequence tasks. Particularly, excelling in natural language processing (NLP). It eliminates RNN and CNN in favor of self ...
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Mar 10, 2025 · 5 min read · Overview Hyperparameter tuning is one of the lifecycle of designing and building machine learning algorithm. Hyperparameter tuning is a process to find the best parameter for algorithm based in our case. Although may not significantly improve the per...
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Dec 27, 2024 · 5 min read · Overview When building and training deep learning models we often facing the problem of overfitting. Overfitting may happen due the model complexity or the model is “memorized” the training dataset instead of learning generalizable patterns. This be...
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Dec 24, 2024 · 8 min read · Overview This dataset is scene classification dataset that published by Intel. This dataset also used in previous implementation. Dataset consist of 6 class that consist of difference categories like buildings, forest, glacier, mountain, sea, and str...
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Dec 24, 2024 · 3 min read · Overview The paper “MobileNet: Efficient Convolutional Neural Network for Mobile Vision Application” authored by Andrew G. Howard, Menglong Zhu, and others in 2017, introduces a new approach for convolutional neural network which is more efficient an...
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