Notes by Louisa
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  • Introduction
  • Chapter1 Python Cheatsheet
  • Chapter2 Java Cheatsheet
  • Chapter3 Algorithm
  • Chapter4 Model
    • Linear Regression
    • Logistic Regression
    • Regularization and Feature Selection
    • Model Evaluation
    • Nonlinear Models
    • PCA
    • Unsupervised Learning
    • Gradient Descent and Gradient Boosting
    • XG Boost and Light GBD
    • Deep Learning
    • Tensorflow/Keras
    • RNN
  • Chapter5 Statistics and A/B Testing
  • Chapter6 SQL
  • Chapter7 Big Data and Spark
  • Chapter8 Code Walk-Throughs
  • Chapter9 Special Topics
  • Project: The Winning Recipes to an Oscar Award
  • Project: A Crime Analysis of the Last Decade NYC
  • Project: Predict User Type Based on Citibike Data
  • GeoSpark/GeoSparkVis for Geospatial Big Data
  • Single Scattering Albedo
  • Sea Ice Albedo Retrievals
  • Lidar Project
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  1. Chapter4 Model

RNN

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Last updated 6 years ago