Matthew Mayo on Muck Rack

Matthew Mayo

Nord-Pas-de-Calais, Ottawa
As seen in: KDnuggets, LinkedIn, Medium, Color Research & Application, Oracle Magazine, Wiley Online Library, Tobacco Control, Flipboard, JAMA (The Journal of the American Medical Association), JAMA: Journal of the American Medical Association, HistoryNet and
Data Scientist | AI Engineer | Digital Strategist Managing Editor for Guiding Tech Media's family of professional data-oriented websites
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Articles

3 NLTK Tricks for Advanced Text Preprocessing & Linguistic Analysis

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By Matthew Mayo, Import Nltk
| KDnuggets Verified
In this article, we will walk through three essential NLTK tricks to elevate your text preprocessing: preserving phrase integrity with the MWETokenizer, context-aware lemmatization with POS mapping, and statistical collocation extraction using association measures. Natural language processing (NLP) has undergone an obvious paradigm shift in recent years, with large language models (LLMs) and transformers handling complex end-to-end understanding tasks.
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3 Pandas Tricks for Data Cleaning & Preparation

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By Matthew Mayo, ' Completed '
| KDnuggets Verified
In this article, we will walk through three essential Pandas tricks to clean and prepare your data efficiently: declarative method chaining, memory and speed optimization via categoricals and vectorized string accessors, and group-aware imputation using .transform(). Data cleaning and preparation are estimated to occupy up to 80% of a data scientist's daily workflow.
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3 NumPy Tricks for Numerical Performance

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By Matthew Mayo
| KDnuggets Verified
In this article, we will cover three essential NumPy tricks to optimize your code: vectorization and broadcasting, in-place operations, and leveraging memory views instead of copies. The Python scientific computing and machine learning ecosystem relies heavily on NumPy. It acts as the performance engine behind libraries like Pandas, Scikit-Learn, SciPy, and PyTorch.
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