Tensorflow is an Open Source Software Library for Machine Intelligence originally developed by researchers and engineers working on the Google Brain Team. Great! We have created an environment and successfully activated it.
Which should return: /Users//anaconda/envs/dataweekends/bin/python You can verify that you are in the correct active environment by typing: which python This will prepend (dataweekends) to your terminal prompt. You can then go ahead and activate the environment typing: source activate dataweekends If all goes to plan at the end you should see this message: # To activate this environment, use: Hit Enter and answer y when prompted to proceed. In a terminal window type: conda create -n dataweekends python=2.7 pandas scikit-learn jupyter matplotlib Let's create an environment for our data science development, we'll call this environment dataweekends, but you can call it with any name you want. An environment solves this problem by allowing your friend to have both versions of the library, 1.0 and 1.2, in two separate environments, so that they do not interfere with one another.
#LEARNING PYTHON ON MAC UPDATE#
So, your friend doesn't want to update the library to 1.2 and would also like to test your script, which requires the upgrade. You ask your friend, and she is currently using version 1.0 of that package, because she uses it as part of another project. Let's say you want to share your code with a friend, but are not sure if she has the same package on her laptop. For example, imagine you developed a short python program that uses version 1.2 of a certain package.
#LEARNING PYTHON ON MAC INSTALL#
It can also query and search the package index and current installation, create new environments, and install and update packages into existing conda environments.Ĭonda environments are coherent collections of packages with specific versions that can be used to ensure portability of your python code. It is a package manager that quickly installs, runs, and updates packages and their dependencies. The guys at Continuum have developed an extremely versatile package manager called conda. Here are a couple of screenshots of key steps:Ĭreate a conda environment for deep learning Once you've downloaded Anaconda, you should install it on your Mac following the instructions provided by the Graphical installer. In Dataweekends workshops we use Python 2.7, because that's what most of our users are already familiar with. A detailed explanation of the differences between 2.7 and 3.x can be found here, and here you can find a discussion about what version to choose. If you are a complete beginner, you may want to start directly with Python 3.x. Despite this, I often recommend to install Python 2.7, because of the larger library support. Python 2.7 is considered legacy, while 3.x is the present and future of Python. Python comes in two major versions: 2.7 and 3.x. The open source version of Anaconda is a high performance distribution of Python and R and includes over 100 of the most popular Python, R and Scala packages for data science. install the required packages in that environmentĪnaconda is the leading open data science platform powered by Python.create a conda environment for your deep learning development.download and install Anaconda Python on your laptop.
#LEARNING PYTHON ON MAC HOW TO#
This is the first of a 4 articles series on how to get you started with Deep Learning in Python.