examples | CPython | |
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143 | 1,319 | |
7,763 | 59,856 | |
0.8% | 1.4% | |
5.3 | 10.0 | |
10 days ago | 7 days ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
examples
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
TensorFlow: An open-source machine learning framework for high-performance numerical computations, especially well-suited for deep learning.
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MLOps in practice: building and deploying a machine learning app
The tool used to build the model per se was TensorFlow, a very powerful and end-to-end open source platform for machine learning with a rich ecosystem of tools. And in order to to create the needed script using TensorFlow Jupyter Notebook was used, which is a web-based interactive computing platform.
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🔥14 Excellent Open-source Projects for Developers😎
10. TensorFlow - Make Machine Learning Work for You 🤖
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GPU Survival Toolkit for the AI age: The bare minimum every developer must know
AI models, particularly those built on deep learning frameworks like TensorFlow, exhibit a high degree of parallelism. Neural network training involves numerous matrix operations, and GPUs, with their expansive core count, excel in parallelizing these operations. TensorFlow, along with other popular deep learning frameworks, optimizes to leverage GPU power for accelerating model training and inference.
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
#2 TensorFlow
- Are there people out there who still like Sam atlman - AI IS AT DANGER
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Tensorflow help
I am on a new ftc team trying to get vision to work. I used the ftc machine learning tool chain but I have yet to get a good result with at best a 10% accuracy rate. I have changed everything possible in the tool chain with little luck. To fix this, I have tried making my own .tflite model using the google colab from https://www.tensorflow.org/. When ever I try to run the same code with my own .tflite model, it gives me the error "User code threw an uncaught exception: IllegalStateException - Error getting native address of native library: task_vision_jni". It gives me the same error with official tensor flow tflite test models, and when I put them on a raspberry pi, both worked just fine. Does anyone have a fix to this error or even just tips for the machine learning toolchain?
CPython
- A library to assist writing memory-unsafe code in "pure" Python
- OpenBSD 7.3 を 7.4 へ アップグレード
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Bitcoin Sentiment Analysis using Python and X (Formerly Twitter)
Thankfully, Python, the go-to coding language for loads of developers, is here to save the day. It's got some awesome features for diving into text sentiment analysis. With cool libraries like Tweepy, we can sift through X(Twitter) data and snag those interesting tweets about Bitcoin. And then there's TextBlob, a clever tool for understanding the sentiment in text. When it's time to clean up and organize all that data, libraries like pandas and numpy are there to help out. And let's not forget about matplotlib, the master of visualisations that can help us see the trends in sentiment crystal clear. Armed with these tools, developers can really dig deep into social media data and figure out what the general public thinks about Bitcoin.
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scrape-yahoo-finance
Web Scraping Tool Development: Develop a Python based web scraping tool capable of extracting data from targeted web pages on Yahoo Finance and presenting the data extracted in a readable format. Our target site relies on AJAX to load and update the data dynamically so we will need a tool that is capable of processing JavaScript.
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Employee Management System using Python.
Dealing with piles of papers or scattered Excel sheets for employee information can be a real headache, right? Well, what if I told you there's a smoother way to handle all that? A system that lets you easily store, update, and find details about your employees in just a few clicks. Sounds neat, doesn't it? In this article, we're going to explore creating an employee management system using Python, Tkinter, and SQLite3.
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Build a Product Receipt Generator using Python.
Python is a versatile tool, and today we're delving into a practical use case that can simplify your daily routines. With the datetime module at your disposal, handling dates and times becomes a breeze, making it perfect for crafting accurate and dynamic product receipts. Whether you're a seasoned Python pro or just starting your coding journey, this article will guide you through each step with ease.
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Build a Music Player with Python
When working in Visual Studio Code (VS Code), create a new Python file for our music player project. It's helpful to have separate files for different parts of your project.
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PEP 744 – JIT Compilation
> It provides a meaningful performance improvement for at least one popular platform (realistically, on the order of 5%).
At first it will not provide a large boost, but it will set the foundations for larger gains in subsequent releases. They link a list of some proposed improvements already underway, with improvement estimates, at https://github.com/python/cpython/issues/115802
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Featured Mod of the Month: Phil Ashby
After that, with the basics of software engineering understood, I would move on to a wider use language, with a bigger ecosystem to employ, most likely Python. This would expose me to large system design / distributed systems and architectural challenges...
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Convert Images Into Pencil Sketch
Have you ever felt like your photos needed a little extra touch to stand out? Well, get ready because we're about to learn a cool Python trick! We're going to take ordinary photos and turn them into awesome pencil sketches using Python and OpenCV. This will make your pictures look like they were drawn by hand!
What are some alternatives?
cppflow - Run TensorFlow models in C++ without installation and without Bazel
RustPython - A Python Interpreter written in Rust
mlpack - mlpack: a fast, header-only C++ machine learning library
ipython - Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
Vulpix - Fast, unopinionated, minimalist web framework for .NET core inspired by express.js
face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
Visual Studio Code - Visual Studio Code
Selenium WebDriver - A browser automation framework and ecosystem.
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Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more