Produktbild: Programming Collective Intelligence

Programming Collective Intelligence Building Smart Web 2.0 Applications

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.09.2007

Verlag

O'Reilly Media

Seitenzahl

334

Maße (L/B/H)

23,3/17,9/2,2 cm

Gewicht

622 g

Sprache

Englisch

ISBN

978-0-596-52932-1

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.09.2007

Verlag

O'Reilly Media

Seitenzahl

334

Maße (L/B/H)

23,3/17,9/2,2 cm

Gewicht

622 g

Sprache

Englisch

ISBN

978-0-596-52932-1

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: Programming Collective Intelligence
  • Inhaltsverzeichnis
    Preface
    1. Introduction to Collective Intelligence
    What Is Collective Intelligence?
    What Is Machine Learning?
    Limits of Machine Learning
    Real-Life Examples
    Other Uses for Learning Algorithms
    2. Making Recommendations
    Collaborative Filtering
    Collecting Preferences
    Finding Similar Users
    Recommending Items
    Matching Products
    Building a del.icio.us Link Recommender
    Item-Based Filtering
    Using the MovieLens Dataset
    User-Based or Item-Based Filtering?
    Exercises
    3. Discovering Groups
    Supervised versus Unsupervised Learning
    Word Vectors
    Hierarchical Clustering
    Drawing the Dendrogram
    Column Clustering
    K-Means Clustering
    Clusters of Preferences
    Viewing Data in Two Dimensions
    Other Things to Cluster
    Exercises
    4. Searching and Ranking
    What's in a Search Engine?
    A Simple Crawler
    Building the Index
    Querying
    Content-Based Ranking
    Using Inbound Links
    Learning from Clicks
    Exercises
    5. Optimization
    Group Travel
    Representing Solutions
    The Cost Function
    Random Searching
    Hill Climbing
    Simulated Annealing
    Genetic Algorithms
    Real Flight Searches
    Optimizing for Preferences
    Network Visualization
    Other Possibilities
    Exercises
    6. Document Filtering
    Filtering Spam
    Documents and Words
    Training the Classifier
    Calculating Probabilities
    A Naïve Classifier
    The Fisher Method
    Persisting the Trained Classifiers
    Filtering Blog Feeds
    Improving Feature Detection
    Using Akismet
    Alternative Methods
    Exercises
    7. Modeling with Decision Trees
    Predicting Signups
    Introducing Decision Trees
    Training the Tree
    Choosing the Best Split
    Recursive Tree Building
    Displaying the Tree
    Classifying New Observations
    Pruning the Tree
    Dealing with Missing Data
    Dealing with Numerical Outcomes
    Modeling Home Prices
    Modeling "Hotness"
    When to Use Decision Trees
    Exercises
    8. Building Price Models
    Building a Sample Dataset
    k-Nearest Neighbors
    Weighted Neighbors
    Cross-Validation
    Heterogeneous Variables
    Optimizing the Scale
    Uneven Distributions
    Using Real Data-the eBay API
    When to Use k-Nearest Neighbors
    Exercises
    9. Advanced Classification: Kernel Methods and SVMs
    Matchmaker Dataset
    Difficulties with the Data
    Basic Linear Classification
    Categorical Features
    Scaling the Data
    Understanding Kernel Methods
    Support-Vector Machines
    Using LIBSVM
    Matching on Facebook
    Exercises
    10. Finding Independent Features
    A Corpus of News
    Previous Approaches
    Non-Negative Matrix Factorization
    Displaying the Results
    Using Stock Market Data
    Exercises
    11. Evolving Intelligence
    What Is Genetic Programming?
    Programs As Trees
    Creating the Initial Population
    Testing a Solution
    Mutating Programs
    Crossover
    Building the Environment
    A Simple Game
    Further Possibilities
    Exercises
    12. Algorithm Summary
    Bayesian Classifier
    Decision Tree Classifier
    Neural Networks
    Support-Vector Machines
    k-Nearest Neighbors
    Clustering
    Multidimensional Scaling
    Non-Negative Matrix Factorization
    Optimization
    A. Third-Party Libraries
    B. Mathematical Formulas
    Index