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Source channel @githubtrending · Post #14712 · May 16

#php#calendar#contacts#crm#crm_platform#crm_system#customer_portal#customer_support#customizable#documents#email_marketing#kanban#leads#open_source#php#platform#sales_automation#single_page_application#support EspoCRM is a free, open-source CRM tool that helps you manage customer relationships by organizing leads, contacts, sales, marketing, and support in one easy-to-use web app. It has a clean interface, customizable features, and a REST API for integration, making it flexible for startups, small businesses, and developers. It automates repetitive tasks, saving time and reducing errors, while providing detailed reports to improve decision-making. Being open-source, it’s cost-effective with no licensing fees, and supported by a helpful community. This means you get a powerful, adaptable CRM that boosts productivity and customer management without high costs[1][3][5]. https://github.com/espocrm/espocrm

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Interesting Planet 🌍

@interesting_planet_facts · Post #1053 · 11/19/2025, 06:11 PM

🌎 In 1977, the Soviet Venera 14 probe recorded mysterious low-frequency “thunder”-like sounds on Venus. Scientists now attribute these to seismic activity or wind interacting with the planet’s dense atmosphere. Venus’s surface winds move slowly, but thick air carries sound much farther than on Earth. ✨ #Venus⚡#sounds⚡#space 👉subscribe Interesting Planet 👉more Channels ​

djangoproject

@djangoproject · Post #255 · 02/02/2017, 06:57 PM

https://github.com/tyiannak/pyAudioAnalysis #pyAudioAnalysis is a Python library covering a wide range of audio analysis tasks. Through pyAudioAnalysis you can: Extract #audio features and representations (e.g. mfccs, spectrogram, chromagram) Classify unknown #sounds Train, parameter tune and evaluate classifiers of audio segments Detect audio events and exclude silence periods from long recordings Perform supervised segmentation (joint segmentation - classification) Perform unsupervised segmentation (e.g. speaker diarization) Extract audio thumbnails Train and use audio regression models (example application: emotion recognition) Apply dimensionality reduction to visualize audio data and content similarities