dplyr
Keras
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dplyr | Keras | |
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40 | 75 | |
4,652 | 60,902 | |
0.6% | 0.6% | |
7.4 | 9.9 | |
16 days ago | 1 day ago | |
R | Python | |
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.
dplyr
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Show HN: Open-source, browser-local data exploration using DuckDB-WASM and PRQL
That's great feedback, thanks!
This tool definitely comes from a place of personal need - beyond just handling large files, I've also never really gelled well with the Excel/Google Sheet model of changing data in place as if you were editing text. I'm a Data Scientist and always preferred the chained data transforms you see in things like dplyr (https://dplyr.tidyverse.org/) or Polars (https://pola.rs/) and I feel this tool maps very closely to the chained model.
Also, thank you for the feature requests! Those would all be very useful - we'll put them on the roadmap.
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IS it possible for a R package to set an R option that only affects that package?
There's an example of how to use zzz.R with a .onload() function to set options in the dplyr code base: https://github.com/tidyverse/dplyr/blob/bbcfe99e29fe737d456b0d7adc33d3c445a32d9d/R/zzz.r
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Calculation within a data table by calling on specific values in two columns
Look at the tidyverse, especially the case_when or mutate functions.
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PSA: You don't need fancy stuff to do good work.
Before diving into advanced machine learning algorithms or statistical models, we need to start with the basics: collecting and organizing data. Fortunately, both Python and R offer a wealth of libraries that make it easy to collect data from a variety of sources, including web scraping, APIs, and reading from files. Key libraries in Python include requests, BeautifulSoup, and pandas, while R has httr, rvest, and dplyr.
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Creating data frame
It looks like your syntax is wrong. I think you’re trying to calculate a new variables in your data frame, or alter an existing column in a data frame. Have a look at the select() function in this reference for the proper syntax to use. https://dplyr.tidyverse.org/ Does that help?
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I'm designing a shirt for a friend, it has 4 embroidered images of things they like/do. One thing is coding, they use R... I'm wondering two things. 1) What's a good image or piece of code or something that I should use? and 2) should I even add it to the design the shirt?
A lot of populat libraries have their own logos. Maybe one of them would be good. Check out dplyr for example: https://dplyr.tidyverse.org/
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Anyone use Python for statistics, particularly DOE or QA/QC? What are your thoughts?
I hope you give it a try when you get a chance: https://dplyr.tidyverse.org/
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Rstudio tidyverse help!
You can read up on the dplyr-verbs here, which I strongly suggest for your exam! In the code examples, you can simply click on any function you don't understand and it will take you directly to the documentation. Good Luck!
- Beginner question
- osdc-2023-assignment1
Keras
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Getting Started with Gemma Models
After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow.
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Keras 3.0
All breaking changes are listed here: https://github.com/keras-team/keras/issues/18467
You can use this migration guide to identify and fix each of these issues (and further, making your code run on JAX or PyTorch): https://keras.io/guides/migrating_to_keras_3/
- Keras 3: A new multi-back end Keras
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Can someone explain how keras code gets into the Tensorflow package?
I'm guessing the "real" keras code is coming from the keras repository. Is that a correct assumption? How does that version of Keras get there? If I wanted to write my own activation layer next to ELU, where exactly would I do that?
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How popular are libraries in each technology
Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks.
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List of AI-Models
Click to Learn more...
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Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!
I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them.
- free categorical predictive analytic software?
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I got advice on building ai apps.
Keras documentation: https://keras.io/
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Mastering Data Science: Top 10 GitHub Repos You Need to Know
3. Keras Keras is a high-level neural networks API written in Python that’s built on top of TensorFlow. It’s designed to enable fast experimentation with deep learning, allowing you to build and train models with just a few lines of code. If you’re new to deep learning or just want a more user-friendly interface, Keras is the way to go.
What are some alternatives?
worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
Rustler - Safe Rust bridge for creating Erlang NIF functions
scikit-learn - scikit-learn: machine learning in Python
ggplot2 - An implementation of the Grammar of Graphics in R
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
nx - Multi-dimensional arrays (tensors) and numerical definitions for Elixir
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
explorer - Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir
tensorflow - An Open Source Machine Learning Framework for Everyone
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.