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https://github.com/vietstartuplondon/wtf-is-machine-learning
Materials and resources for "WTF is... Machine Learning?"
https://github.com/vietstartuplondon/wtf-is-machine-learning
ipynb jupyter-notebook machine-learning notebook python slide
Last synced: 3 months ago
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Materials and resources for "WTF is... Machine Learning?"
- Host: GitHub
- URL: https://github.com/vietstartuplondon/wtf-is-machine-learning
- Owner: VietStartupLondon
- Created: 2017-11-17T10:36:16.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2017-11-22T10:57:22.000Z (about 7 years ago)
- Last Synced: 2024-10-11T15:41:25.906Z (3 months ago)
- Topics: ipynb, jupyter-notebook, machine-learning, notebook, python, slide
- Language: Jupyter Notebook
- Homepage:
- Size: 5.4 MB
- Stars: 7
- Watchers: 7
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# WTF is Machine Learning by VietStartup London
Materials for the [WTF is Machine Learning](https://www.facebook.com/events/726163544245558) event held on November 18, 2017 by [VietStartup London](https://www.facebook.com/groups/284739328332602/).
## Programme
- 10:00-11:00: Basics of Machine Learning ([video](https://www.facebook.com/famanson/videos/10214249173963589/), [slides](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/assets/Basics%20of%20ML.pdf))
- 11:00-11:15: Coffee Break
- 11:15-12:00: Cracking the Love Codes ([video](https://www.facebook.com/famanson/videos/10214249173963589/), [slides](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/assets/Crack%20the%20Love%20Codes.pdf))
- 12:00-13:00: Break
- 13:00-14:00: Linear Regression ([notebook](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/LinearRegression.ipynb), [hard notebook](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/LinearRegressionHard.ipynb), [answers](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/LinearRegressionAnswers.ipynb))
- 14:00-15:00: Logistic Regression ([slides](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/assets/Logistic%20Regression.pdf), [notebook](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/LogisticRegression.ipynb), [hard notebook](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/LogisticRegressionHard.ipynb), [answers](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/LogisticRegressionAnswers.ipynb))
## How to get started
For the event attendees, please make sure that you complete steps 1-7 below.
1. Download Anaconda distribution Python version 3.6 from [https://www.anaconda.com/download](https://www.anaconda.com/download).
2. Follow the installation instructions for your system on [https://docs.anaconda.com/anaconda/install](https://docs.anaconda.com/anaconda/install).
3. Download this project using this link: [https://github.com/VietStartupLondon/wtf-is-machine-learning/archive/master.zip](https://github.com/VietStartupLondon/wtf-is-machine-learning/archive/master.zip)
4. Move the zip file to your Documents folder and unzip it.
5. Start a new terminal (in Linux or Mac Os) or command promt (In Windows, press Start > Run > type in `cmd`), and enter:
```
jupyter notebook
```
6. A new tab should open in your browser with the Jupyter notebook application running on `localhost:8888`. Navigate to the folder in Documents containing the project "wtf-is-machine-learning".
7. Open up "IntroductionToPython.ipynb" to familiarise yourself with Python and Jupyter notebook. Pay particular attention to section 6 in the notebook but don't sweat over it too much. We will help you during the session.
8. You can then proceed with the notebook 'LinearRegression.ipynb', followed by 'LogisticRegression.ipynb'. If you are up for a challenge try the Hard version instead.
## [Further Resources](https://github.com/VietStartupLondon/wtf-is-machine-learning/blob/master/assets/ml-resources.md)
This event was organized by (in alphabetical order):
- [Dat Nguyen](https://github.com/dkn22)
- [Manh Dao](https://github.com/manhdao)
- [Phuong Hoa Giang](https://github.com/HoaGiangcorp)
- [Son Pham](https://github.com/famanson)
- [Thinh Truong Ha](https://github.com/thinhha)
- [Tuan Anh Le](https://github.com/tanhle)
- [Tuan Anh Le](https://github.com/tuananhle7)
- [Tuan-Minh Nguyen](http://tuanminh.co/)