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Machine learning

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.

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transformers
GaelVaroquaux
GaelVaroquaux commented Feb 7, 2022

Describe the issue linked to the documentation

Many legitimate notebook style examples have been broken, and specifically by the following PR
scikit-learn/scikit-learn#9061

List of examples to update

Note for maintainers: the content between begin/end_auto_generated is updated automatically by a script. If you edit it by hand your changes may be revert

Easy Documentation good first issue
julia
complyue
complyue commented Apr 23, 2022

https://github.com/JuliaLang/julia/blob/3cff21e725097673f969c19f8f0992c9a0838ab3/base/arrayshow.jl#L584

Seems the following change is reasonable:

-            sprint(show_type_name, unwrap_unionall(eltype_X).name), false # Print "Array" rather than "Array{T,N}"
+            sprint(show_type_name, unwrap_unionall(eltype_X).name; context=io), false # Print "Array" rather than "Array{
good first issue display and printing

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

  • Updated Apr 3, 2022
  • Python
trivialfis
trivialfis commented Dec 13, 2020

Currently many more Python projects like dask and optuna are using Python type hints. With the Python package of xgboost gaining more and more features, we should also adopt mypy as a safe guard against some type errors and for better code documentation.

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