Code in this talk can be found here https://github.com/halidebey/PyCon2018
Speaker made use of this tool, Kaggle – https://www.kaggle.com/ – the place to do data science projects.
Speaker refers to this source of data
https://www.figure-eight.com/data-for-everyone/
Discussed the approaches to machine learning
- supervised/non supervised
- Ignoring parts of your dataset
- interesting Python libraries – pandas – https://pypi.org/project/pandas/ and nltk – https://pypi.org/project/nltk/ sklearn (superseded by scikit-learn https://pypi.org/project/scikit-learn/)
- exploring data
Need some information about statistics and algorithms, a such as LogisticRegression.