|4 days ago||2 months ago|
|Apache License 2.0||MIT License|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
CS Internship Questions
1 project | reddit.com/r/stanford | 7 May 2022
By the way, most of the time XGBoost works just as well for projects, would not recommend applying deep learning to every single problem you come across, it's something Stanford CS really likes to showcase when it's well known (1) that sometimes "smaller"/less complex models can perform just as well or have their own interpretive advantages and (2) it is well known within ML and DS communities that deep learning does not perform as well with tabular datasets and using deep learning as a default to every problem is just poor practice. However, if you do (god forbid) get language, speech/audio, vision/imaging, or even time series models then deep learning as a baseline is not the worst idea.
OOM with ML Models (SKlearn, XGBoost, etc), workaround/tips for large datasets?
1 project | reddit.com/r/MLQuestions | 1 Mar 2022
xgboost VS CXXGraph - a user suggested alternative
2 projects | 28 Feb 2022
'y contains previously unseen labels' (label encoder)
1 project | reddit.com/r/pythonhelp | 9 Dec 2021
We haven't tracked posts mentioning LightFM yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
Surprise - A Python scikit for building and analyzing recommender systems
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
tensorflow - An Open Source Machine Learning Framework for Everyone
Keras - Deep Learning for humans
catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
mlpack - mlpack: a scalable C++ machine learning library --
implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets
spotlight - Deep recommender models using PyTorch.
MLflow - Open source platform for the machine learning lifecycle