Skip to content
#

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.

Here are 70,046 public repositories matching this topic...

julia
o314
o314 commented Oct 23, 2021
using Test
@test :(1 = 2) |> repr == Expr(:(=), 1, 2) |> repr == ":(1 = 2)"

but others (reserved) assignment ops are not shown as they are typed, eg in infix form but in prefix one.

@test :(1 := 2) |> repr == ":($(Expr(:(:=), 1, 2)))"

a small annoyance, but one that may easily be fixed by adding them to expr_infix_wide @ https://github.com/JuliaLang/juli

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.

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 May 13, 2021
  • Python
Wikipedia
Wikipedia