COMPSCI 689 Advanced Machine Learning

• Syllabus
• Also the grader for this course
• Assignments
  • Spectral Clustering
  • Label Propagation

COMPSCI 682 Neural Networks: A Modern Introduction

• Assignments
  • Image Classification, kNN, SVM, Softmax, Neural Network
  • Fully-Connected Nets, Batch Normalization, Dropout, Convolutional Nets
  • Image Captioning, Fooling Images, Image Generation, Deep Dream

COMPSCI 690N Advanced Natural Language Processing

• Assignments
  • Shift-Reduce Dependency Parser
  • NER using CRFs
  • Relation Extraction
  • EM Algorithm- Aggregate latent class bigram model

COMPSCI 688 Probabilistic Graphical Models

• Assignments
  • Heart disease prediction model
  • OCR using CRFs
  • Image Denoising and Gibbs Sampling

COMPSCI 585 Intro to Natural Language Processing

• Assignments
  • Naive Bayes Sentiment Classifier for IMDB reviews
  • POS Tagging
  • HMM-Viterbi Algorithm
  • Text generation using n-grams

COMPSCI 590D Algorithms for Data Science

• Clustering
• Estimating Statistical Properties of Data
• Near Neighbor Search
• Algorithms over Massive Graphs and Social Networks
• Learning Algorithms
• Randomized Algorithms
• Assignments
  • Reservoir Sampling
  • Count-min Sketch
  • Map Reduce
  • Locality Sensitve Hashing

COMPSCI 590S Systems for Data Science

• Parallelism: Threads, message-passing , Fault-tolerance
• Large-Scale Analytics: MapReduce / Hadoop
• Distributed computing, Cloud Computing, “Big Data”
• Databases: SQL, database architectures, optimization, consistency, NoSQL, key-value stores, consistent hashing (Redis, MongoDB)
• Optimizing MapReduce: FlumeJava
• Storage: Google File System / HDFS
• Parallel Processing: Spark SQL, TensorFlow,Dynamo
• Distributed Shared Memory, Data Warehousing, BigTable

COMPSCI 645 Database Design and Implementation

• Relational Algebra, SQL, Datalog
• Storage and Indexing
• Query processing and optimization
• FDs and normalization
• Transactions and concurrency
• OLAP
• Data understanding, fairness,diversity, and transparency
• Security & Database Theory

Online/Audited/Self

• Reinforcement Learning (David Silver, John Schulmann)
• Machine Learning (Andrew Ng)
• Recommender Systems (Yong Feng)