One part of my bucket list for 2018 is finishing the Udacity Course UD120: Intro to Machine Learning.
The host of this course are Sebastian Thrun, ex-google-X and founder of Udacity and Katie Malone, creator of the Linear digressions podcast.
The course consists of 17 lessons. Every lesson has a couple of hours of video and lots and lots of quizzes in it.
- [x] Lesson 1: Only introduction 🙂
- [x] Lesson 2: Naive Bayes
- [x] Lesson 3: Support Vector Machines
- [x] Lesson 4: Decision Trees
- [x] Lesson 5: Choose your own algorithm
- [x] Lesson 6: Datasets and questions
- [x] Lesson 7: Regression
- [x] Lesson 8: Outliers
- [x] Lesson 9: Clustering
- [x] Lesson 10: Feature Scaling
- [ ] Lesson 11: Text Learning
- [ ] Lesson 12: Feature Selection
- [ ] Lesson 13: PCA
- [ ] Lesson 14: Validation
- [ ] Lesson 15: Evaluation Metrics
- [ ] Lesson 16: Tying it all together
- [ ] Lesson 17: Final project
