python anaconda install

Recently used Anaconda more, because it inside the package is very full AH. If the next native Python is to be used, you have to install it yourself.But some packages are dependent on each other and are really crazy when they are loaded. The lazy man thought of Anaconda's set of suits.Here's the problem: Anaconda can o

Recently, we have been using Python for Chinese natural language processing. The IDE is PyCharm. PyCharm is indeed the first choice for Python development, but it is still lacking in scientific computing. For this reason, I have tried EnthoughtCanopy, But Canopy feels complicated and it is not convenient to manage Python extensions. Until today I found

Anaconda is a Python release for scientific computing that supports Linux, MAC, Windows, and Python packages that contain a number of popular scientific calculations and data analysis. The most tedious of Python learning is the management of different versions and libraries, and

The tutorials on the web are varied and similar. I had some problems with my installation, so I summed up a blog post.Sublime text is a lightweight, cross-platform, textual editor that expands its capabilities through the package.There are a lot of packages that build the Python environment, where I install the Anaconda package.1. Sublime Text Download: HTTP://WW

Anaconda multi-Environment multi-version python configuration operation method, anacondapython Conda test Guide Before starting this conda test, you should have downloaded and installed Anaconda or Miniconda. Note: After installation, you should close and re-open the windows command line. I. Conda test process: Use conda. First, we will confirm that you have inst

One, the required installation packageBecause Scikit-image is based on scipy, installing NumPy and scipy is sure. To display the picture, you also need to install the Matplotlib package, combined, the required packages are:1 Python >= 2.62 Numpy >= 1.6.13 cython >= 0.214 Six >=1.45 SciPy >=0.96 matplotlib >= 1.1.07 networkx >= 1.88 Pillow >= 1.7.89 Dask[array ] >= 0.5.0Comparison, installation is very cumbe

blogger himself in learning machine learning process, see the related books use Python version is different, but want to each version can know how to use, next, bloggers to introduce a more simple and convenient way: First: Install the Python environment, highly recommended to use Anaconda,

The little woman is not, can not solve in the anaconda environment to compile Caffe, also can not solve in Anaconda environment install TensorFlow, so can only be used with a python, a will use Anaconda Then, if you modify the file in ~/.BASHRC, that is, add the export path=

Recently, we have been using Python for Chinese natural language processing. The IDE is PyCharm. PyCharm is indeed the first choice for Python development, but it is still lacking in scientific computing. For this reason, I have tried EnthoughtCanopy, but Canopy feels complicated. Managing Python extension Anaconda is

Anaconda, in short, is a packaged Python collection with package management and environmental management tools and Python packages for data science computing. Download and install https://www.anaconda.com/download/#macos from here. After the installation is complete, set the path as follows: # Add the

Anaconda is a scientific computing environment similar to canopy, but it is more convenient to use. The Package Manager Conda is also very powerful. The first is to download the installation. Anaconda provides two versions of Python2.7 and Python3.4, and can be created by Conda if additional versions are required. When the installation is complete, you can see that Ana