ggplot2
examples
ggplot2 | examples | |
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62 | 143 | |
6,328 | 7,754 | |
0.5% | 0.7% | |
9.4 | 5.3 | |
6 days ago | 29 days ago | |
R | Jupyter Notebook | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
ggplot2
- ggplot2
- Ask HN: How do you build diagrams for the web?
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Visualizing shapefiles in R with sf and ggplot2!
ggplot2
- Ask HN: What plotting tools should I invest in learning?
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Relative frequency of letters in five-letter English words (Wordle aid) [OC]
I got the list of five-letter words from the words package in R, created the QWERTY keyboard grid with base R and tibble, and visualized the data with geom_tile in the ggplot2 package.
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[OC] U.S. News & World Report Best Colleges: 2002 to 2023
Thanks, it's an interesting idea! I definitely could implement this with scale_fill_gradientn) in ggplot2.
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Facts about Aaron Boone's Ejections as Manager
I used the ggplot2 package in R to create these figures.
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Fueling Innovation and Collaborative Storytelling
This might not be at the top of your list, but science fiction often presents advanced data analysis and visualization technologies. Open source data analysis tools such as Python's Pandas and R's ggplot2 have revolutionized the field, making complex data manipulation and visualization accessible to all. In the science fiction novel The Martian, astronaut Mark Watney uses a variety of data analysis and visualization tools to survive on Mars. He uses Python's Pandas to clean and organize data, and he uses R's ggplot2 to create visualizations of his data. These tools allow him to make sense of the vast amounts of data and help him to make critical decisions about his survival.
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[OC] Visualizing Financial Market Returns Across Many Asset Classes via Heatmaps
Sorry about the slow reply, but the auto-moderator seems to be deleting my comments (for some unknown reason). I will try once more: the geom_tile function in ggplot2.
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[OC] Forbes List of Highest-Earning Musicians: 1987 to 2021
Visual cues are a much better idea, thanks! Unfortunately, I don't know how to do that in ggplot2, either (I created these figures in R).
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?
What are some alternatives?
Altair - Declarative statistical visualization library for Python
cppflow - Run TensorFlow models in C++ without installation and without Bazel
tmap - R package for thematic maps
mlpack - mlpack: a fast, header-only C++ machine learning library
vega - A visualization grammar.
awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
dplyr - dplyr: A grammar of data manipulation
face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
Selenium WebDriver - A browser automation framework and ecosystem.
glue - Glue strings to data in R. Small, fast, dependency free interpreted string literals.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing