STA141C: Big Data & High Performance Statistical Computing
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1 STA141C: Big Data & High Performance Statistical Computing Lecture 0: Course information Cho-Jui Hsieh UC Davis April 3, 2018
2 Course Information Website: STA141C_Spring2018/main.html My office: Mathematical Sciences Building (MSB) 4232 Office hours: 1pm 2pm Tuesday My TA: Chun-Jui (Gary) Chen Justin Wang
3 Course Information The goal of this: How to write a good program for data analytics Learn to implement statistical models for big data Learn to use some open source (python) tools How to parallelize your code We ll use python for this course
4 Course Structure Statistical Programming (in python) We assume you already know how to use python Basic algorithms and data structure, and how to use them in python Numerical Optimization for Statistical Problems Briefly review basic optimization algorithms How to use them to solve real world problems linear regression, classification, neural network Parallel Computing in Python Multicore computing Distributed computing Numerical Linear Algebra for Statistics Matrix decomposition for huge matrices PageRank, Clustering, Word2vec Feature generation Text, images
5 Prerequisites Basic python programming skill (STA 141B or ECS python course) Basic math and statistics (linear algebra, matrix multiplication, eigen-decomposition)
6 Grading Policy Grading Policy Homework (65%) Final project (35%) Homeworks: Homework will be some programming problems You ll need to write a report for each homework. Use python to write the programming part. Final project: Form a group of 4 people Work on a real data mining problem or a data mining contest. Project proposal due at the 5-th week (TBD) Final project report due at the end of this quarter (TBD)
7 Discussion sessions No discussion sessions for the first week Later on TAs will be giving some tutorial or reviewing homework solutions in discussion sessions.
8 Preview: Numerical Optimization for Statistical Problems Statistical Programming (in python) Numerical Optimization for Statistical Problems Parallel Computing in Python Numerical Linear Algebra for Statistics Feature generation
9 Preview: Numerical Optimization for Statistical Problems Optimization: min f (w) w f : objective function to be optimized
10 Preview: Numerical Optimization for Statistical Problems Optimization: min f (w) w f : objective function to be optimized Example: linear regression n min (w T x i y i ) 2 w i=1
11 Preview: Numerical Optimization for Statistical Problems Optimization: min f (w) w f : objective function to be optimized Example: linear regression n min (w T x i y i ) 2 w Generalize to arbitrary loss: min w i=1 n loss(w T x i y i ) 2 i=1
12 Preview: Numerical Optimization for Statistical Problems Optimization: min f (w) w f : objective function to be optimized Example: linear regression n min (w T x i y i ) 2 w Generalize to arbitrary loss: min w i=1 n loss(w T x i y i ) 2 i=1 Generalize to arbitrary function: n min loss(g w (x i ) y i ) 2 w i=1
13 Preview: Numerical Optimization for Statistical Problems (Iterative) algorithms: Gradient descent Stochastic gradient descent Block-coordinate descent
14 Preview: Numerical Optimization for Statistical Problems (Iterative) algorithms: Gradient descent Stochastic gradient descent Block-coordinate descent Implement to solve large problems
15 Preview: Numerical Optimization for Statistical Problems Statistical Programming (in python) Numerical Optimization for Statistical Problems Parallel Computing in Python Numerical Linear Algebra for Statistics Feature generation
16 Preview: Parallel Computing in Python Basic concept for multicore/distributed parallelism How to implement (multi-core) parallelism in python
17 Preview: Numerical Optimization for Statistical Problems Statistical Programming (in python) Numerical Optimization for Statistical Problems Parallel Computing in Python Numerical Linear Algebra for Statistics Feature generation
18 Numerical Linear Algebra for Statistics SVD, eigen-decomposition How to decompose huge matrices Applications PageRank, Clustering, Word2vec
19 Preview: Numerical Optimization for Statistical Problems Statistical Programming (in python) Numerical Optimization for Statistical Problems Parallel Computing in Python Numerical Linear Algebra for Statistics Feature generation
20 Feature generation Features for text data Features for image data
21 Coming up Numpy programming, basic algorithm/data structure Questions?
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