Preview

mgrani-LODA-lecture-notes-on-data-analysis-2cd9d90
- .gitignore
  
  43 Bytes
- 0.INTRO
  - Course-Web Mining Project (5944P).ipynb
    
    41.4 kB
  - images
    - 10SteamGraph2.jpg
      
      102.1 kB
    - flu-trends.png
      
      103.9 kB
    - twitter example.png
      
      90.6 kB
    - web-data-infographic.jpeg
      
      135.7 kB
- I.Data-Science-in-Python
  - DSiP-1-Introduction.ipynb
    
    34.3 kB
  - DSiP-2-Python-Programing-Basics.ipynb
    
    124.7 kB
  - DSiP-3-Numpy.ipynb
    
    238.7 kB
  - DSiP-4-Scipy.ipynb
    
    316.2 kB
  - DSiP-5-Matplotlib.ipynb
    
    1.7 MB
  - DSiP-6-Pandas.ipynb
    
    552.3 kB
  - DSiP.bib
    
    803 Bytes
  - DSiP.bib.bak
    
    65 Bytes
  - data
    - 311-service-requests.csv
      
      55.1 MB
    - cordisfp7noabstracts.xls
      
      8.7 MB
    - iris.dat
      
      4.6 kB
    - weather_data.csv
      
      212 Bytes
  - exercises
    - Exercise DSiP-2-1-Python Standard Data Structures.ipynb
      
      25.1 kB
    - Exercise DSiP-3-1-Numpy.ipynb
      
      22.6 kB
    - Exercise DSiP-5-1-Analysing the Iris Dataset with Mathplotlib-.ipynb
      
      211.7 kB
    - Exercise DSiP-6-1-Pandas-NYC-Open-Data.ipynb
      
      147.1 kB
  - filename.png
    
    32.0 kB
  - filename.svg
    
    15.0 kB
  - images
    - 4-Vs-of-big-data.jpg
      
      804.2 kB
    - 600px-Fayyad96kdd-process.png
      
      75.6 kB
    - github-diff.png
      
      109.6 kB
    - github-project-page.png
      
      117.3 kB
    - gitk.png
      
      149.8 kB
    - ipython-notebook-screenshot.jpg
      
      560.4 kB
    - ipython-screenshot.jpg
      
      157.4 kB
    - optimizing-what-2.png
      
      19.3 kB
    - optimizing-what.png
      
      33.9 kB
    - python namespaces.png
      
      12.3 kB
    - python-screenshot.jpg
      
      140.7 kB
    - scientific-python-stack.png
      
      43.8 kB
    - scientific-python-stack.svg
      
      12.6 kB
    - spyder-screenshot.jpg
      
      596.6 kB
    - theory-experiment-computation.png
      
      126.2 kB
    - theory-experiment-computation.svg
      
      12.4 kB
  - mymodule.py
    
    560 Bytes
  - mymodule.pyc
    
    1.1 kB
  - random-matrix.csv
    
    72 Bytes
  - random-matrix.npy
    
    152 Bytes
  - scripts
    - hello-world-in-german.py
      
      43 Bytes
    - hello-world.py
      
      45 Bytes
  - stockholm_td_adj.dat
    
    2.9 MB
- II.ML-and-DM
  - AUTO
    - data
      
      30.3 kB
    - description
      
      1.7 kB
  - CAR
    - data
      
      51.9 kB
    - description
      
      3.1 kB
  - II.ML-DM-Simple-Regression.ipynb
    
    22.9 kB
  - II.ML-and-DM-Example-DecisionTree.ipynb
    
    145.3 kB
  - II.ML-and-DM-Example-LMS.ipynb
    
    204.3 kB
  - II.ML-and-DM-Example-Regression.ipynb
    
    346.5 kB
  - II.ML-and-DM-Stacked-Denoising-Autoencoders.ipynb
    
    1.1 MB
  - II.ML-and-DM-in-a-Nutshell-with-scikitlearn-Supervised-Learning.ipynb
    
    364.2 kB
  - II.ML-and-DM-in-a-Nutshell-with-scikitlearn-clustering.ipynb
    
    343.4 kB
  - II.ML-and-DM-in-a-Nutshell-with-scikitlearn-overview-and-preprocessing.ipynb
    
    46.3 kB
  - II.ML-and-DM-in-a-Nutshell-with-scikitlearn-projections-and-manifold-learning.ipynb
    
    369.8 kB
  - images
    - pca-1.pdf
      
      3.6 kB
    - pca-2.pdf
      
      10.5 kB
    - pca-3.pdf
      
      12.5 kB
    - pca-center.pdf
      
      13.2 kB
    - pca-example-1D-of-2D.png
      
      13.3 kB
    - pca-princip.svg
      
      12.0 kB
    - pca-rotate.pdf
      
      21.6 kB
    - pca-transform.svg
      
      4.0 kB
    - pca-variance.svg
      
      3.6 kB
  - modules
    - plot_classification.py
      
      1.6 kB
    - plot_cluster_comparison.py
      
      3.9 kB
    - plot_iris_logistic.py
      
      1.3 kB
    - plot_kmeans_digits.py
      
      3.5 kB
    - plot_svm_margin.py
      
      1.8 kB
- III.NLP
  - III.NLP-with-NLTK-Short-Intro.ipynb
    
    189.8 kB
  - exercise
    - III.NLTK-Intro-Exercise.ipynb
      
      143.2 kB
  - images
    - NER Pipelin.png
      
      18.0 kB
- IV.Visual-Analytics
  - .DS_Store
    
    6.1 kB
  - IV.VA-InformationVisualisation-with-JavaScript-and-3DJs.ipynb
    
    50.7 kB
  - data-auto.csv
    
    19.7 kB
  - images
    - ascomb-scatter.svg
      
      10.4 kB
    - ascomb.png
      
      60.6 kB
    - ascomb.svg
      
      5.2 kB
    - coordinate-system.svg
      
      545 Bytes
    - svg-stub.html
      
      375 Bytes
  - solutions.zip
    
    5.8 kB
- README.md
  
  8.8 kB
- V.Web-Mining-Applications
  - V.WMA-Crawling-Twitter.ipynb
    
    258.0 kB
  - exercises
    - Exercise - Clustering Twitter Data.ipynb
      
      15.5 kB
    - Exercises Crawling Twitter with Python.ipynb
      
      36.9 kB
    - images
      - twitter-app-ii.png
        
        146.6 kB
      - twitter-app-iii.png
        
        88.6 kB
      - twitter-app-iv.png
        
        92.3 kB
      - twitter-app.png
        
        76.8 kB
      - twitter-example.png
        
        309.9 kB
  - images
    - OAuth.svg
      
      5.2 kB
    - twitter-example.png
      
      309.9 kB
    - twitter-maxid-problem.png
      
      69.6 kB
    - twitter-paging-max_id.png
      
      67.8 kB
    - twitter-paging-problem.png
      
      62.6 kB
    - twitter-paging-since_id.png
      
      74.7 kB
  - projects
    - twitter
      - V.WMA-Project-Shitstorm-Detection-on-Twitter.ipynb
        
        6.7 kB
      - V.WMA-Project-Topic-Detection.ipynb
        
        7.7 kB
    - web-crawling
      - V.WMA-Project-Web-Page-Genre-Classification.ipynb
        
        6.6 kB
  - python-twitter

LODA-lecture-notes-on-data-analysis-1.0.1.zip