#python#ai#deep_learning#filetype#keras_classification_models#keras_models#mime_types#onnx
Magika is a fast AI tool from Google that detects file types with ~99% accuracy across 200+ formats, using a tiny model that works in milliseconds on one CPU. Install easily via pip, brew, or scripts for CLI/Python/JS/Go use; scan files, directories, or streams with options like JSON output or recursion. It boosts your safety by routing files to scanners, like in Gmail/Drive, helping spot threats quickly without size limits.
https://github.com/google/magika
http://www.aparat.com/v/0scM5
Irene Chen A Beginner's Guide to Deep Learning.
What is #Deep_Learning ? It has recently exploded in popularity as a complex and incredibly powerful tool. This talk will present the basic concepts underlying deep learning in understandable pieces for complete beginners to #machine_learning.
http://www.aparat.com/v/Corus
Advanced users #Deep_Learning, anyone who has followed #machine_learning over the past years has heard it. In this talk I will go past the hype and show what deep learning actually means and how one goes about solving complex machine learning task with a minimum amount of code, with the help of theano, an amazing python library for deep learning.
https://www.analyticsvidhya.com/blog/2016/08/deep-learning-path/?utm_content=bufferd56c5&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer
#Deep_Learning, a prominent topic in #Artificial_Intelligence domain, has been in the spotlight for quite some time now. It is especially known for its breakthroughs in fields like Computer Vision and Game playing (Alpha GO), surpassing human ability. Since the last survey, there has been a drastic increase in the trends. (click here to check out the survey)
Here is what Google trends shows us:
https://github.com/BVLC/caffe
#Caffe is a #deep_learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.
Maid - Mobile Artificial Intelligence Distribution
Maid is a cross-platform free and an open-source application for interfacing with llama.cpp models locally, and remotely with Ollama, Mistral, Google Gemini and OpenAI models remotely.
-Choose from A wide range of models that runs LOCALLY and access remote models via api key!
-Text based output
-Image Generation (Selected Models only)
-No video or short clips generation yet
-Voice generation on selected models (Not tested)
-Setting model parameters
-Setting system prompt (Making the model behave/generate output in a certain way).
-And more.
Get it on
Github - https://github.com/Mobile-Artificial-Intelligence/maid/releases/latest
Fdroid - https://f-droid.org/packages/com.danemadsen.maid/
Spystore - https://play.google.com/store/apps/details?id=com.danemadsen.maid
*Don't clear CACHE OF THE APP AND EXCLUDE IT FROM SYSTEM'S AUTO CACHE CLEANING as app stores everything in device cache*
Follow @nogoolag and @libreware for more
#ai
Cherry Studio
Cherry Studio is a desktop client for Windows, Mac and Linux, which supports many LLM providers, including large cloud services and local models.
Among its main functions is the ability to work with more than 300 pre -designed #AI assistants, the creation of custom assistants, as well as support for various formats of documents, including text, images and office files.
The application offers tools for global search, top management and translating, which significantly improves interaction with the user thanks to the cross -platform and many settings options.
https://github.com/cherryhq/cherry-studio
LibreChat AI
Open-source platform that allows users to chat and interact with various #AI models through a unified interface. You can use OpenAI, Gemini, Anthropic and other AI models using their API. You may also use Ollama as an endpoint and use LibreChat to interact with local LLMs. It can be installed locally or deployed on a server.
LibreChat is designed to be highly customizable and supports a wide range of AI providers and services. Let me summarize its main features:
Free and Open Source: Accessible to everyone without any costs.
Customization: Offers extensive options to tailor the platform to individual preferences.
Multi-AI Support: Integrates with numerous AI models and services.
Unified Interface: Provides a consistent experience for interacting with different AI models.
https://www.librechat.ai
https://itsfoss.com/librechat-linux/
Jan.ai
https://jan.ai
A platform that enables you to run self-hosted local #AI. Jan provides an OpenAI-equivalent API server at localhost:1337 that can be used as a drop-in replacement with compatible apps.
With Jan, you can:
-Run open-source LLMs locally or connect to cloud AIs like ChatGPT or Google.
-Search the web and databases.
Integrate AI with everyday tools to work on your behalf (with permission).
-Customize and add features with Extensions.
Jan is opinionated software about what AI should be.
https://www.analyticsvidhya.com/learning-paths-data-science-business-analytics-business-intelligence-big-data/learning-path-data-science-python/
Comprehensive learning path – #Data_Science in Python
Journey from a Python noob to a Kaggler on Python
So, you want to become a data scientist or may be you are already one and want to expand your tool repository. You have landed at the right place. The aim of this page is to provide a comprehensive learning path to people new to python for data analysis. This path provides a comprehensive overview of steps you need to learn to use Python for #data_analysis. If you already have some background, or don’t need all the components, feel free to adapt your own paths and let us know how you made changes in the path.
You can also check the mini version of this learning path
#Deep_Learning