To write code & run the Jupyter notebooks immediately without needing to install anything on your computer, click on the "launch binder" badge above. For more on Binder, go here.
If you're planning to code along, make sure to clone, download, or re-pull this repository on the morning of Friday 12/01. All edits will be completed by end of day ET Thursday 11/31.
with Hugo Bowne-Anderson. Follow him on twitter @hugobowne
After a successful first Facebook Live Coding session, DataCamp's very own Hugo Bowne-Anderson is back in front of the camera! This time, Hugo will take you from zero to one with machine learning to make several submissions to Kaggle's (in)famous Titanic machine learning competition. The goal will be to build an algorithm that predicts whether any given passenger on the Titanic survived or not, given data on them such as the fare they paid, where they embarked and their age. You'll do so using the Python programming language, Jupyter notebooks and state-of-the-art packages such as pandas, scikit-learn and seaborn. Alongside Hugo, you'll dive into this rich dataset and build your chops in exploratory data analysis, data munging and cleaning, and machine learning. No previous experience with machine learning necessary. Join us for this live, interactive code along.
Join Hugo live on Friday 12/01 at 10:30am ET on Facebook!
Not a lot. It would help if you knew
- programming fundamentals and the basics of the Python programming language (e.g., variables, for loops);
- a bit about
pandasand DataFrames; - a bit about Jupyter Notebooks;
- your way around the terminal/shell.
However, I have always found that the most important and beneficial prerequisite is a will to learn new things so if you have this quality, you'll definitely get something out of this code-along session.
Also, if you'd like to watch and not code along, you'll also have a great time and these notebooks will be downloadable afterwards also.
If you are going to code along and use the Anaconda distribution of Python 3 (see below), I ask that you install it before the session.
Note: We may be making some live submissions to Kaggle so, if you want to do that, get yourself an account before the session.
To get set up for this live coding session, clone this repository. You can do so by executing the following in your terminal:
git clone https://github.com/datacamp/datacamp_facebook_live_titanic
Alternatively, you can download the zip file of the repository at the top of the main page of the repository. If you prefer not to use git or don't have experience with it, this a good option.
If you do not already have the Anaconda distribution of Python 3, go get it (n.b., you can also do this w/out Anaconda using pip to install the required packages, however Anaconda is great for Data Science and I encourage you to use it).
Navigate to the relevant directory datacamp_facebook_live_titanic and install required packages in a new conda environment:
conda env create -f environment.yml
This will create a new environment called fb_live_titanic. To activate the environment on OSX/Linux, execute
source activate fb_live_titanic
On Windows, execute
activate fb_live_titanic
In the terminal, execute jupyter notebook.
Then open the notebook 1-titanic_EDA_first_models.ipynb and we're ready to get coding. Enjoy.
The code in this repository is released under the MIT license. Read more at the Open Source Initiative. All text remains the Intellectual Property of DataCamp. If you wish to reuse, adapt or remix, get in touch with me at hugo at datacamp com to request permission.