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The Seq2Seq( sequence to sequence) model is a special class of RNNs used to solve complex language problems.
In this article we explain Focal Loss which is an improved version of Cross-Entropy Loss, that tries to handle the class imbalance problem.
Understand, how you can quickly start detecting objects in images of your own, using the YOLO v1 architecture on the Google Colab platform, in no time.
Understand NLG concepts such as dataset preparation, how a neural language model is trained, and finally Natural Language Generation process in PyTorch.
Neural Networks from scratch Python and R tutorial covering backpropagation, activation functions, and implementation from scratch.
MobileBERT introduces bottlenecks in the transformer blocks, which allows us easily to distill the knowledge from larger teachers into smaller students.
Learn the different ways to split a decision tree in machine learning: Information Gain, Gini Impurity, Reduction in Variance & Chi-Square.
Learn about tokenization in NLP and its significance in understanding text. Discover how it aids sentiment analysis and named entity recognition.
Compare Random Forest and Decision Tree algorithms through detailed explanations, Python examples, and insights on model performance.
A beginners guide for machine learning with C++. In this article learn about linear and logistic regression and how to implement them using C++.
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