Libraries tagged by train

Convert strings between 13 naming conventions: Snake case, Camel case, Pascal case, Kebab case, Ada case, Train case, Cobol case, Macro case, Upper case, Lower case, Sentence case, Title case and Dot notation.

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Agile Core - collection of PHP Traits for designing object-oriented frameworks

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Convert strings from and to AdaCase, CamelCase, CobolCase, KebabCase, Lowercase, MacroCase, PascalCase, SentenceCase, SnakeCase, TitleCase, TrainCase, and Uppercase

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Easily convert between camelCase, PascalCase, kebab-case, snake_case, SCREAMING_SNAKE_CASE, Train-Case, and string case!

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Laravel client for Replicate predictions, files, models, trainings, and signed webhooks

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Easily convert between camelCase, PascalCase, kebab-case, snake_case, SCREAMING_SNAKE_CASE, Train-Case, and string case!

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NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, grammar and spelling correction, keywords and keyphrases extraction, chatbot, product description and ad generation, intent classification, text generation, image generation, code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, speech synthesis, embeddings, and dependency parsing. It is ready for production, served through a REST API. This is the PHP client for the API. More details here: https://nlpcloud.com. Documentation: https://docs.nlpcloud.com. Github: https://github.com/nlpcloud/nlpcloud-php

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Клиент API РЖД: поиск поездов, вагоны и места, маршруты, цены

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OpenStreetMap field for Filament forms with Leaflet.js — pick coordinates, geocode addresses, and store points in 11 formats (WKT, GeoJSON, array, DMS, map URLs)

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PHP SDK for e-conomic

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A drop in query builder for Laravel models.

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A Livewire wrapper for FullCalendar.

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A PHP library for seamless interaction with Yandex GPT (Generative Pre-trained Transformer) API, providing text generation, tokenization, and embedding functionalities.

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An example project using a multi layer feed forward neural network for text sentiment classification trained with 25,000 movie reviews from IMDB.

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Train and run classifiers that score how hard a prompt is for an LLM to answer.

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