Copy and paste the code below into the grey box on your Jupyter notebook: print("Hello World!") To begin, let’s write code that will display some words when we run it. ![]() This helps us perhaps look at any intermediate output from our program. Jupyter notebooks allow us to write snippets of code and then run those snippets without running the full program. Browser window pop-upĬongratulations - you’ve created your first Jupyter notebook! Now it’s time to write some code. On the top right, click on New and select “Python 3”: Click on New and select Python 3Ī new browser window should pop up like this. If you navigate to the folder, your browser should look something like this: Navigating to a folder called Intuitive Deep Learning Tutorial on my Desktop I’m going to create a folder on my Desktop called “Intuitive Deep Learning Tutorial”. Jupyter Notebook allows us to run Python code interactively on the web browser, and it’s where we will be writing most of our code.Ī browser window should open up with your directory listing. You should see a front page like this: Anaconda Navigator Home ScreenĬlick on ‘Launch’ under Jupyter Notebook, which is the second panel on my screen above. Once the installation is done, go to your Start Menu and you should see some newly installed software: You should see this on your start menuĬlick on Anaconda Navigator, which is a one-stop hub to navigate the apps we need. Once it has finished downloading, just go through the setup step by step as follows: Click Next Click “I Agree” Click Next Choose a destination folder and click Next Click Install with the default options, and wait for a few moments as Anaconda installs Click Skip as we will not be using Microsoft VSCode in our tutorials Click Finish, and the installation is done! A pop up should appear for you to click “Save” into whatever directory you wish. This tutorial will be using Python 3, so click the green Download button under “Python 3.7 version”. Be sure to click on “Windows” as your Operating System (or whatever OS that you are on) to make sure that you are downloading the correct version. This tutorial is written specifically for Windows users, but the instructions for users of other Operating Systems are not all that different. Visit this page: and scroll down to see this: Download Anaconda The first step is to download Anaconda, which you can think of as a platform for you to use Python “out of the box”. ![]() The main programming language we are going to use is called Python, which is the most common programming language used by Deep Learning practitioners. Once you’ve set up the above, you can build your first neural network to predict house prices in this tutorial here:īuild your first Neural Network to predict house prices with Keras Setting up Anaconda and Jupyter Notebook Create Anaconda environments and install packages (code that others have written to make our lives tremendously easy) like tensorflow, keras, pandas, scikit-learn and matplotlib.This post will guide you through in a step-by-step manner how to set up Python for your Data Science and Deep Learning projects. How do we get everything started in the first place so that we can plug-and-play Data Science or Deep Learning code? A common complaint I hear from complete beginners is that it’s pretty difficult to set up Python. If you’re a beginner to Python and you want to embark on this journey, then this post will guide you through your first steps. Perhaps you might have thought: “Well, if it’s really that easy, then why don’t I try it out myself?” You may have seen some of this code on Data Science / Deep Learning blog posts. ![]() ![]() This is not an exaggeration many programmers out there have done the hard work of writing tons of code for us to use, so that all we need to do is plug-and-play rather than write code from scratch. You can code your own Data Science or Deep Learning project in just a couple of lines of code these days. By Joseph Lee Wei En How to get started with Python for Deep Learning and Data Science A step-by-step guide to setting up Python for a complete beginner
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