Main Content

• Books
  • An Introduction to Statistical Learning, with Applications in R, Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (Springer, 2013).
  • Python Data Science Handbook, Essential Tools for Working with Data, Jake VanderPlas (O'Reilley, November 2016)
  • The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd Edition), Trevor Hastie, Robert Tibshirani, and Jerome Friedman (Springer, 2009)
  
  
• Communities and Websites
  • Data Science Central: The Online Resource for Big Data Practitioners [LinkedIn]
  • Towards Data Science: Sharing concepts, ideas and codes
  
  
• Datasets
  • Datasets for "The Elements of Statistical Learning"
  • Kaggle [Competitions]
  • UCI Machine Learning Repository
  • v7labs Open Datasets
  
  
• Journals
  • SIAM Journal on Mathematics of Data Science (SIMODS)
  
  
• Languages / Tools / Libraries
  • C, Python, CUDA
  • StarPU, ScalFMM
  • cuBLAS, CUDA Math Library, cuSPARSE, cuSOLVER
  • Tensorflow, PyTorch
  
  
• Videos / On-Line Courses
  • In-depth introduction to machine learning in 15 hours of expert videos