DBS Intro to Machine Learning

Hello class!

Class slack: https://dbs-ml.slack.com

Daily Schedule

	Lecture & Lab
Week 1	Instruction Time: 215m • Day 1 introduction (10m) • Machine Learning Intro (40m) • Pandas Intro (90m) • Optional: Python Review (75m)
Week 2	Instruction Time: 150m • Linear Regression Theory Intro (60m) • Linear Regression Code Intro (90m)
Week 3	Instruction Time: 170m • Cross Validation (60m) • Complexity Intro (50m) • Regularization (60m)
Week 4	Instruction Time: 210m • Stochastic Gradient Descent (60m) • Time Series (150m)
Week 5	Instruction Time: 120m • Class Imbalance (60m) • KNN Classification Intro (60m)
Week 6	Instruction Time: 135m • Classification And Regression Trees (60m) • Ensembling (75m)
Week 7	Instruction Time: 110m • Model Complexity (20m) • SVM (90m)
Week 8	Instruction Time: 85m • Clustering K-means Intro (40m) • Clustering K-Means Lab (45m)
Week 9	Instruction Time: 110m • Big Data Prep (10m) • Neural Net Intro (100m)
Week 10	Instruction Time: 120m • Big Data Overview (60m) • Recommendation Systems (60m)
Week 11	Instruction Time: 165m • Hadoop Hive (105m) • Spark Intro (60m)
Week 12	Instruction Time: 200m • Pair: Placeholder (0m) • Pyspark Lab (200m)