Wei (Serena) Zou's repositories
univariate-linear-regression
Example data science project used in Datacamp's Unit Testing for Data Science in Python course
grokking_algorithms
Code for the book Grokking Algorithms (https://amzn.to/29rVyHf)
Agile_Data_Code_2
Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Deep-learning-and-Neural-Network
This project includes all assignments completed for the DL and NNs classes offered by Andrew Ng on deeplearning.ai
Implementation-of-the-Frank-Wolfe-Algorithm
The purpose this project is to implement the Frank-Wolfe Algorithm for transportation network analysis. The next section summarizes the key steps involved in the Python coding process, followed by two traffic assignment applications. The report is concluded with a discussion of findings and future plans.
Uber-Pick-Up-Time-Series-Models
The objective of this study is to predict the demand for uber pick-ups in the Manhattan area using time series models.
SQL-Exercises
MS SQL codes, topics include select, sort, wildcard characters, string operators, calculated fields, group by clause, aggregate functions, crosstabing, conditional data manipulation, union operations, type conversion functions, update, delete, joins, sub-queries, stored procedures and triggers
Data-Mining-Logistic-Regression-and-Kernel-Regression
This project implemented the stochastic gradient descent (SGD) algorithm for logistic regression, given a training set and a testing set.
Data-Mining-Support-Vector-Machine-using-the-Sequential-Minimals-Optimization-Algorithm
The goal of this piece of code is to implement a simplified version of the Sequential Minimal Optimization (SMO) algorithm by John Platt to train SVMs in the dual formulation.
Data-Mining-Diagonals-in-High-Dimensions
The purpose of this code is to compute the empirical probability mass function (EPMF) for the random variable X that represents the angle (in degrees) between any two diagonals in high dimensions.
Data-Mining-Kernel-PCA
This piece of code is used to implement the Kernel PCA (KPCA) algorithm.
ProgrammingAssignment2
Repository for Programming Assignment 2 for R Programming on Coursera