Collective Intelligence
"Programming Collective Intelligence: Building Smart Web 2.0 Applications" by Toby Segaran
This repo contains exercises that I found interesting to explore from the book. I the book structure was kept.
Chapter 2 - Recomendation Systems
- Find best links for people from a social bookmarking site
- Movie recommendation system from the MovieLens dataset.
Chapter 3 - Clustering
- Find groups on a set of popular web blogs
- Find people's desires from a social networking web site.
Chapter 4 - Searching and Planning
- Development of a Search engine including the crawler, indexer, and query engine.
- PageRank algorithm for scoring pages based on inbound links
- Create a neural network that learns which keywords are associated with different results.
Chapter 5 - Optimization
- Find best flights for a group of people traveling to the same location
- Find the best way of matching students to dorms
Chapter 6 - Bayesian Filtering
- Spam filters for automatically classifying documents based on the type of words and other features
Chapter 7 - Decision Trees
- Predict whether or not a user is likely to become a premium subscriber.
Chapter 8 - KNN Clustering
- Classifications using k-nearest neighbors techniques.
- System for predicting eventual auction prices for items based on a set of properties.
Chapter 9 - SVM
- Match people in online dating sites or when searching for professional contacts.
Chapter 10 - NNM Factorization
- Find the independent features in a dataset.
Chapter 11 - Genetic Programing
- Builds algorithms using evolutionary ideas to solve a particular problem.
Setup
To run all available scripts locally you must create a new environment and install and required packages:
$ mkvirtualenv collective-intelligence
$ pip install -r requirements.txtIf you don't have
mkvirtualenvinstalled, you can find it here: Install mkvirtualenv
License
All code here is under the MIT license.
Disclaimer
All code in this repo is for educational purpuses only. Use this programs at your own risk.