![]() ![]() No module named 'numpy.distutils._msvccompiler' in numpy.distutils trying from distutilsįile "C:\Users\Public\Documents\Wondershare\CreatorTemp\pip-install-8ooeas1k\scikit-learn\setup.py", line 290, in įile "C:\Users\Public\Documents\Wondershare\CreatorTemp\pip-install-8ooeas1k\scikit-learn\setup.py", line 286, in setup_packageįile "c:\users\admin\appdata\local\programs\python\python38-32\lib\site-packages\numpy\distutils\core.py", line 137, in setupįile "C:\Users\Public\Documents\Wondershare\CreatorTemp\pip-install-8ooeas1k\scikit-learn\setup.py", line 174, in configurationįile "c:\users\admin\appdata\local\programs\python\python38-32\lib\site-packages\numpy\distutils\misc_util.py", line 1033, in add_subpackageĬonfig_list = self.get_subpackage(subpackage_name, subpackage_path,įile "c:\users\admin\appdata\local\programs\python\python38-32\lib\site-packages\numpy\distutils\misc_util.py", line 999, in get_subpackageĬonfig = self._get_configuration_from_setup_py(įile "c:\users\admin\appdata\local\programs\python\python38-32\lib\site-packages\numpy\distutils\misc_util.py", line 941, in _get_configuration_from_setup_pyĬonfig = setup_nfiguration(*args)įile "sklearn\setup.py", line 76, in configuration Partial import of sklearn during the build process. errorĮRROR: Command errored out with exit status 1:Ĭommand: 'c:\users\admin\appdata\local\programs\python\python38-32\python.exe' -u -c 'import sys, setuptools, tokenize sys.argv = '"'"'C:\\Users\\Public\\Documents\\Wondershare\\CreatorTemp\\pip-install-8ooeas1k\\scikit-learn\\setup.py'"'"' _file_='"'"'C:\\Users\\Public\\Documents\\Wondershare\\CreatorTemp\\pip-install-8ooeas1k\\scikit-learn\\setup.py'"'"' f=getattr(tokenize, '"'"'open'"'"', open)(_file_) code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"') f.close() exec(compile(code, _file_, '"'"'exec'"'"'))' bdist_wheel -d 'C:\Users\Public\Documents\Wondershare\CreatorTemp\pip-wheel-jm5hdzgz' -python-tag cp38Ĭwd: C:\Users\Public\Documents\Wondershare\CreatorTemp\pip-install-8ooeas1k\scikit-learn\ Requirement already satisfied: joblib>=0.11 in c:\users\admin\appdata\local\programs\python\python38-32\lib\site-packages (from scikit-learn->sklearn->mlrose) (0.14.0)īuilding wheels for collected packages: scikit-learnīuilding wheel for scikit-learn (setup.py). Requirement already satisfied: numpy in c:\users\admin\appdata\local\programs\python\python38-32\lib\site-packages (from mlrose) (1.17.4) Requirement already satisfied: scipy in c:\users\admin\appdata\local\programs\python\python38-32\lib\site-packages (from mlrose) (1.3.2) All rights reserved.Ĭ:\Users\admin>pip install mlrose Collecting mlrose I am new to machine learning, so a detailed explaination will be appreciated. There are ways to bulk install everything you need using PIP, And PIP only installs what we demand/command from the terminal, nothing additional stuff, unless we ask for it.Īlso, keep in mind, if you want to do data science, ML, Deep learning things, go for 64-bit version of python, so that every module you need can be installed without countering errors.Whenever I pip install mlrose, it is showing me the following error. Unless you have a significant benefit when doing so, which could be more pronounced for those in a professional environment. So, if your machine is slow and you have less space, Anaconda is a big NO-NO for you.Īnaconda (IMHO) is a finely tuned hype in the internet space of beginner python users.Īnd even if you have sufficient memory and a capable device, I don't find why should you spend that for things that you may never use. When you use conda command to install a python package, it usually pulls additional (maybe unnecessary for a beginner) packages along with it, thus consuming more & more space on your device. usually occupies 2-4 GB of space very easily.(There is a light installer known as miniconda, but it too goes on to consume memory considerably) (Otherwise you'll have to be specific and observant of where is it that the new python packages being installed on your computer.)Ĭonda dist. If you still want to have conda on your machine, go for it, but if you have python pre-installed, remove it first, and then use conda. If you're a beginner, and don't intend to do some comprehensive stuff in data science/ML field, I don't see any reason that you will need to install Anaconda. Anaconda distribution has been on my computer for last 2 years, on & off, so I feel that I have some experience using it.Īnaconda tries to be a Swiss army knife, and the fact remains, everything that is available with anaconda, can be manually installed using PIP. ![]()
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