arthur/ml_exercises
1
0
Fork 0
mirror of https://github.com/ArthurDanjou/ml_exercises.git synced 2026-01-14 12:14:38 +01:00
Code Issues Packages Projects Releases Wiki Activity

minor

Browse Source
This commit is contained in:
franzi
2021-08-18 20:46:17 +02:00
parent b553363a86
commit 1c004c78ff
1 changed files with 3 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
README.md
View File

@@ -2,7 +2,7 @@
This repository contains the Python exercises accompanying the theory from my [machine learning book](https://franziskahorn.de/mlbook/). This repository contains the Python exercises accompanying the theory from my [machine learning book](https://franziskahorn.de/mlbook/).
You might also want to have a look at the [cheat sheet](https://github.com/cod3licious/ml_exercises/blob/main/cheatsheet.pdf), which includes a summary of the most important steps when developing a machine learning solution, incl. code snippets. You might also want to have a look at the [cheat sheet](/cheatsheet.pdf), which includes a summary of the most important steps when developing a machine learning solution, incl. code snippets.
If you're unfamiliar with Python, please have a look at [this tutorial](https://github.com/cod3licious/python_tutorial) before working on the exercises, which also includes some notes on how to install Python and Jupyter Notebook on your own computer (please make sure you're using Python 3 and all libraries listed in the `requirements.txt` file are installed and up to date; you can verify this with the `test_installation.ipynb` notebook). <br> If you're unfamiliar with Python, please have a look at [this tutorial](https://github.com/cod3licious/python_tutorial) before working on the exercises, which also includes some notes on how to install Python and Jupyter Notebook on your own computer (please make sure you're using Python 3 and all libraries listed in the `requirements.txt` file are installed and up to date; you can verify this with the `test_installation.ipynb` notebook). <br>
If you have a Google account, you can also run the code in the cloud using **Google Colab**: If you have a Google account, you can also run the code in the cloud using **Google Colab**:
@@ -32,7 +32,7 @@ Have fun!
##### Block 1.3: ##### Block 1.3:
- [ ] Read the whole chapter: ["Data & Preprocessing"](https://franziskahorn.de/mlbook/_data_preprocessing.html) - [ ] Read the whole chapter: ["Data & Preprocessing"](https://franziskahorn.de/mlbook/_data_preprocessing.html)
- [ ] Answer [Quiz 2](https://forms.gle/Pqr6EKHNxzrWb7MF9) - [ ] Answer [Quiz 2](https://forms.gle/Pqr6EKHNxzrWb7MF9)
- [ ] Read the first part of the chapter ["ML Algorithms: Unsupervised & Supervised Learning"](https://franziskahorn.de/mlbook/_ml_algorithms_unsupervised_supervised_learning.html) - [ ] Read the first section of the chapter ["ML Algorithms: Unsupervised & Supervised Learning"](https://franziskahorn.de/mlbook/_ml_algorithms_unsupervised_supervised_learning.html)
--- ---
@@ -49,7 +49,7 @@ Have fun!
##### Block 2.3: ##### Block 2.3:
- [ ] Read the section: ["Supervised Learning: Overview"](https://franziskahorn.de/mlbook/_supervised_learning_overview.html) - [ ] Read the section: ["Supervised Learning: Overview"](https://franziskahorn.de/mlbook/_supervised_learning_overview.html)
- [ ] Answer [Quiz 3](https://forms.gle/uzdzytpsYf9sFG946) - [ ] Answer [Quiz 3](https://forms.gle/M2dDevwzicjcHLtc9)
--- ---