Searching Engine Optimization
The process of maximizing the number of visitors to a particular website by ensuring that the site appears high on the list of results returned by a search engine.
Legiti
IR System Components
Further Scoring Ideas
Parametric indeed: Fields & Zones
Fields
Thus far, a doc has been a sequence of terms
However, in fact, documents have multiple parts, with special semantics
Unranked Retrieval Evaluation
Precision, Recall, and F Measure
Precision: P = relevant / retrieved
Recall: R = retrieved / relevant
Usually precision and recall are binary assessments (increasing one
Stored Procedure
DELIMITER $
CREATE PROCEDURE how_is_it (IN x INT)
BEGIN
IF (x > 5) then
SELET CONCAT(x, is higher) AS answer;
ELSE
SELECT CONCAT(x, is lower) AS answer;
END IF;
END $
DELIMITER ;
Optimization
Whenever I see star, DO NOT first do a query to check if the start exists (using a SELECT statement) IT IS TOO SLOW!
Use in-memory hash map (stars, movies, etc)
Before inserting something
Edit distance
Definition: the minimum number of single character operations
3 operations allowed per character:
Add a character
Delete a character
Substitute a character
DROP FUNCTION IF EXISTS ed;
C
1 - Introduction
2 - Universal Usability and Normans Principles
Universal usability: design for the widest range of abilities and the widest range of situations (design for diversity)
3 levels of proc
R System Components
Further Scoring Ideas
Parametric indeed: Fields & Zones
Fields
Thus far, a doc has been a sequence of terms
However, in fact, documents have multiple parts, with special semantics
Week 5
Tuesday: Responsive Design
Tuesday: Breakpoints, Media Queries and Mobile First
IR System Evaluations
Evaluating in IR System
Introduction
Main idea: more relevant results => happier user => go
PageRank
Introduction
PageRank scoring is a way of measuring the importance of website pages
Idea: more important websites are likely to receive more links
Use long-term steady state as links scores
C
Midterm Review
Know the different learners
Know the different loss functions
Bias & Variance:
Bias: how much I have restricted the class to a small se t; how capable your model is at capturing the tru
COMPSCI 177: Applications of Probability in Computer Science
University of California, Irvine, Fall 2017
Probability and statistics play a key role in real-world applications of computer science. Exam
Last Modified: January 11, 2018
CS 178: Machine Learning: Winter 2018
Homework 1
Due Date: Thursday, January 18, 2018
This homework (and many subsequent ones) involves data analysis, and discussion of
+
CS178: Machine Learning and Data Mining
Introduction
Prof. Erik Sudderth
Some materials courtesy Alex Ihler & Sameer Singh
Artificial Intelligence (AI)
Building intelligent systems
Lots of parts t
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CS178: Machine Learning and Data Mining
Bayesian Classifiers & Nave Bayes
Prof. Erik Sudderth
Some materials courtesy Alex Ihler & Sameer Singh
Machine Learning
Bayesian Classification
Nave Bayes
Ba
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CS178: Machine Learning and Data Mining
Complexity & Nearest Neighbor Methods
Prof. Erik Sudderth
Some materials courtesy Alex Ihler & Sameer Singh
Machine Learning
Complexity and Overfitting
Neares
C HAPTER
7
FT
VC Dimension
Definitions
RA
Up to this point, we have talked generally about the complexity or flexibility of our learner, or the
set of functions it is able to approximate, without bein
C HAPTER
8
FT
Decision trees
Decision trees are another popular and powerful function type for supervised learning. One advantage of
decision trees is that they produce very interpretable decision rul
C HAPTER
5
FT
Linear classification
We next turn our attention to using linear models for classification, in which we are required to make a
discrete prediction (or decision) about a data point given
C HAPTER
3
FT
Nearest Neighbor Methods
3.1
RA
A very simple class of learners are nearest neighbor models. In essence, nearest neighbor methods reflect
the most basic concept of prediction: if we wish
CS 122A : Introduction to Data Management-Assignment 2
Fall 2017
In this assignment, your task is mapping the ER design (given to you at the end of this
document) into the relational model. Please no
CS 122A Course Assignment 5
SQL Constraints, Triggers, Views
Fall 2017
Due: Tuesday, November 28th (11:59 pm)
For Problem 1 you do not need to use mysql, however for Problem 2 and
Problem 3 you should
CS 122A Course Assignment 4
SQL Queries
Fall 2017
Due: Monday, November 20 (11:59 pm)
SQL Queries (100 points)
For answering the following questions, use the script provided to you. The script contain
CS 122A : Introduction to Data Management-Assignment 3
Fall 2017
You are required to work on this assignment in teams of three.
Deadline : Tuesday, November 7th 11:59 PM
Functional Dependencies
1)
CS 122A : Introduction to Data Management-Assignment 1
Fall 2017
While working on your CS122A course assignments you will gain experience in database modeling, design,
loading, querying and updates.
Lecture 10: Vector Algebra: Orthogonal Basis
Orthogonal Basis of a subspace
Computing an orthogonal basis for a subspace using Gram-Schmidt
Orthogonalization Process
1
Orthogonal Set
Any set of vec