Hackers Realm Blog

Hackers Realm

Extract Features from Image using Pretrained Model | Deep Learning | Python

Extracting features from images using a pre-trained model is common technique in transfer learning which saves time and improve performance.

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Text Preprocessing Techniques in NLP | Complete Tutorial | Python

Text preprocessing involves cleaning and transforming raw text data into a format that is more suitable for analysis and machine learning

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Word Embedding using GloVe | Feature Extraction | NLP | Python

Explore GloVe word embedding for NLP in Python. Learn feature extraction, transforming words into vector representations. #GloVe #Python

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Feature Extraction using Word2Vec | NLP | Python

Word2Vec is a NLP technique for learning word embeddings which are dense numerical representations of words in a continuous vector space

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Feature Extraction using Term Frequency - Inverse Document Frequency (TF-IDF) | NLP | Python

TF-IDF is a numerical representation often used in NLP and information retrieval to evaluate the importance of a word in a document

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Feature Extraction of Text Data using Bag of Words | NLP | Python

A bag-of-words is a representation of text that describes the occurrence of words within a document.

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Dimensionality Reduction using PCA vs LDA vs t-SNE vs UMAP | Machine Learning | Python

Explore Dimensionality Reduction: PCA vs LDA vs t-SNE vs UMAP in Python. Compare techniques to transform high-dimensional data.

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Ensemble Techniques in Machine Learning | Python

Boost model performance with Ensemble Techniques in Python. Explore bagging, boosting, & stacking to create powerful machine learning models

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Handle Imbalanced classes in Dataset | Machine Learning | Python

Handling imbalanced classes involves applying techniques such as resampling, class weighting, and algorithm selection to mitigate the bias.