- Dataquest 의 온라인 강의 함께듣기 스터디
- 일시 : 2017.07 ~ 2017.10
- 인원 : 5명
- 스터디 방식
- 일주일에 두개의 미션을 학습하고, 각자의 위키에 학습내용을 요약 정리 한다.
- 미션별로 한명이 다른사람들이 작성한 내용을 정리하여 위키 페이지에 정리하고 스터디 시간에 리뷰한다.
- https://www.dataquest.io/course/machine-learning-fundamentals
- mission1. Introduction To K-Nearest Neighbors
- mission2. Evaluating Model Performance
- mission3. Multivariate K-Nearest Neighbors
- mission4. Hyperparameter Optimization
- mission5. Cross Validation
- mission6. Guided Project: Predicting Car Prices
- https://www.dataquest.io/course/calculus-for-machine-learning
- mission1. Understanding Linear And Nonlinear Functions
- mission2. Understanding Limits
- mission3. Finding Extreme Points
- https://www.dataquest.io/course/linear-algebra-for-machine-learning
- mission1. Linear Systems
- mission2. Vectors
- mission3. Matrix Algebra
- mission4. Solution Sets
- https://www.dataquest.io/course/linear-regression-for-machine-learning
- mission1. The Linear Regression Model
- mission2. Feature Selection
- mission3. Gradient Descent
- mission4. Ordinary Least Squares
- https://www.dataquest.io/course/machine-learning-intermediate
- mission1. Logistic Regression
- mission2. Introduction To Evaluating Binary Classifiers
- mission3. Multiclass Classification
- mission4. Intermediate Linear Regression
- mission5. Overfitting
- mission6. Clustering Basics
- mission7. K-Means Clustering
- mission8. Gradient Descent
- mission9. Introduction To Neural Networks
- mission10. Guided Project: Predicting The Stock Market