add link to 2018 blog post
parent
4330470990
commit
e43b96424a
|
@ -4,9 +4,9 @@ This video series will teach you how to solve machine learning problems using Py
|
|||
|
||||
There are **9 video tutorials** totaling 4 hours, each with a corresponding **Jupyter notebook**. The notebook contains everything you see in the video: code, output, images, and comments.
|
||||
|
||||
You can [watch the entire series](https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A) on YouTube, and [view all of the notebooks](http://nbviewer.jupyter.org/github/justmarkham/scikit-learn-videos/tree/master/) using nbviewer.
|
||||
**Note:** The notebooks in this repository have been updated to use Python 3.6 and scikit-learn 0.19.1. The original notebooks (shown in the video) used Python 2.7 and scikit-learn 0.16, and can be downloaded from the [archive branch](https://github.com/justmarkham/scikit-learn-videos/tree/archive). You can read about how I updated the code in this [blog post](https://www.dataschool.io/how-to-update-your-scikit-learn-code-for-2018/).
|
||||
|
||||
**Note:** The notebooks in this repository have been updated to use Python 3.6 and scikit-learn 0.19.1. The original notebooks (shown in the video) used Python 2.7 and scikit-learn 0.16, and can be downloaded from the [archive branch](https://github.com/justmarkham/scikit-learn-videos/tree/archive).
|
||||
You can [watch the entire series](https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A) on YouTube, and [view all of the notebooks](http://nbviewer.jupyter.org/github/justmarkham/scikit-learn-videos/tree/master/) using nbviewer.
|
||||
|
||||
[![Watch the first tutorial video](images/youtube.png)](https://www.youtube.com/watch?v=elojMnjn4kk&list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A&index=1 "Watch the first tutorial video")
|
||||
|
||||
|
|
Loading…
Reference in New Issue