You can learn about scikit-learn which contains many algorithms for machine learning. See some of the extra utilties scikit-learn offers such as model evaluation, parameter selection and more.
- [Instructor] Sci-kit learn…is a package for machine learning.…It implements a lot of algorithms…for tasks such as classification, regression,…clustering, and more.…Apart from providing algorithms,…sci-kit learn also provides a lot of utilities…to help us with day to day machinery tasks.…Such as data processing, parameter selection,…model evaluation, and more.…Sci-kit learn accommodation is one of the best…there is in the open source world.…For example, for people who are new at machine learning,…there's a choosing and estimator section.…
You can follow the chart until you find…the right algorithm to your problem.…So let's say I find the linear SVC is what I want.…I can click on it and jump directly…to the connotation of linear SVC.…Sci-kit learn is huge and has many parts.…I'm going to show you some of the more interesting parts…and also teach you some of the guidelines…to help you use and understand it.…The developers of sci-kit learn…tried to make the API consistent…so once you learn one algorithm,…it's pretty easy to use the rest of them.…
- Working with Jupyter notebooks
- Using code cells
- Extensions to the Python language
- Markdown cells
- Editing notebooks
- NumPy basics
- Broadcasting, array operations, and ufuncs
- Folium and Geo
- Machine learning with scikit-learn
- Plotting with matplotlib and bokeh
- Branching into Numba, Cython, deep learning, and NLP
Skill Level Intermediate
1. Scientific Python Overview
2. The Jupyter Notebook
3. NumPy Basics
Manage environments5m 11s
6. Folium and Geo
7. NY Taxi Data
10. Other Packages
11. Development Process
Next steps1m 33s
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