Multifuntional toolkit
Grasp is a lightweight AI toolkit for Python, with tools for data mining, natural language processing, machine learning and network analysis. It has 300+ fast and essential algorithms, with ~25 lines of code per function, self-explanatory function names, no dependencies.
OSINT
Textgain Academy offers hands-on Grasp training courses for interested OSINT researchers. It comes bundled with an optional data visualization engine (40KB) for rendering 2D graphics.
Toolkits for data mining and NLP
Grasp is a multifunctional toolkit with tools for data mining, including downloading and processing html, finding ready-to-process wikipedia articles and twitter opinions, as well as easily deploying API’s. The natural language processing toolkit includes tools for language identification, finding words, sentences, and word types, as well as determining the polarity of a text.
Toolkits for network analysis and ML
Grasp’s network analysis toolkit includes seamless functions to map and visualise networks. The machine learning toolkit includes algorithms to quantify text, train models, and retrieve predictions. Machine Learning (ML) algorithms learn by example. If you show them 10K spam and 10K real emails (i.e., train a model), they can predict whether other emails are also spam or not. Each training example is a {feature: weight} dict with a label. For text, the features could be words, the weights could be word count, and the label might be real or spam.
Toolkits for good and comfort
A big concern in AI is bias introduced by human trainers. Grasp has tools to explain how & how and why a ML model makes decisions. Grasp also includes tools for comfort, such as efficient date, path, and CSV handling.
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