courses:psaw:lab_ml

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Next revision		 Previous revision
courses:psaw:lab_ml [2022/05/20 17:27] – created - external edit 127.0.0.1courses:psaw:lab_ml [2025/03/31 15:04] (current) – [Learn more!] jeremi
Line 10: Line 10:
 ==== Materials ==== ==== Materials ====
  
-  - Q&A Session -- Instead of a lecture, a short series of keywords to "warm up" (based on the textbook):+  - Q&A Session -- a short series of keywords to "warm up" (based on the textbook):
     - What is the difference between supervised learning, unsupervised learning, and reinforcement learning?     - What is the difference between supervised learning, unsupervised learning, and reinforcement learning?
     - What is the difference between regression and classification?     - What is the difference between regression and classification?
Line 29: Line 29:
   - Advanced practice session:   - Advanced practice session:
     - If you want to tackle additional topics, do the optional Advanced section in both notebooks. This will give you the opportunity to generate artificial features (for linear regression) and learn about decision trees (for classification problems).     - If you want to tackle additional topics, do the optional Advanced section in both notebooks. This will give you the opportunity to generate artificial features (for linear regression) and learn about decision trees (for classification problems).
-  - Report: +
-    - Send the final versions of both notebooks (to download them, click in Google Colab: ''File > Download > Download .ipynb''). Make sure you have done obligatory part, i.e., **4 tasks** (in Regression) and **6 tasks** (in Classification).+
  
 ==== Learn more! ==== ==== Learn more! ====
Line 40: Line 39:
   * [[https://www.kdnuggets.com/2018/04/10-machine-learning-algorithms-data-scientist.html|Ten Machine Learning Algorithms You Should Know to Become a Data Scientist]]   * [[https://www.kdnuggets.com/2018/04/10-machine-learning-algorithms-data-scientist.html|Ten Machine Learning Algorithms You Should Know to Become a Data Scientist]]
   * [[http://www.kdnuggets.com/2017/05/guerrilla-guide-machine-learning-python.html|The Guerrilla Guide to Machine Learning with Python]] ("a complete course for the quick study hacker with no time (or patience) to spare")   * [[http://www.kdnuggets.com/2017/05/guerrilla-guide-machine-learning-python.html|The Guerrilla Guide to Machine Learning with Python]] ("a complete course for the quick study hacker with no time (or patience) to spare")
-  * [[https://www.lenwood.cc/2014/05/13/12-free-data-mining-books/|14 Free (as in beer) Data Mining Books]]+  * FIXME [[https://www.lenwood.cc/2014/05/13/12-free-data-mining-books/|14 Free (as in beer) Data Mining Books]]
   * ML courses at Coursera.org:   * ML courses at Coursera.org:
     * [[https://www.coursera.org/learn/machine-learning|Machine learning]]     * [[https://www.coursera.org/learn/machine-learning|Machine learning]]
Line 46: Line 45:
     * [[https://www.coursera.org/specializations/jhu-data-science|Data Science specialization]]     * [[https://www.coursera.org/specializations/jhu-data-science|Data Science specialization]]
  
-  * [[https://www.kdnuggets.com/2018/03/what-machine-learning-isnt.html|What Machine Learning Isn't]]+  * [[https://steelkiwi.com/blog/what-is-machine-learning/|What is Machine Learning and What is It Not?]]
  • courses/psaw/lab_ml.1653067632.txt.gz
  • Last modified: 3 years ago
  • by 127.0.0.1