First, the visualization method
- Bar chart
- Pie chart
- Box-line Diagram (box chart)
- Bubble chart
- Histogram
- Kernel density estimation (KDE) diagram
- Line Surface Chart
- Network Diagram
- Scatter chart
- Tree Chart
- Violin chart
- Square Chart
- Three-dimensional diagram
Second, interactive tools
- Ipython, Ipython Notebook
- plotly
Iii. Python IDE Type
- Pycharm, specifying a Java swing-based user interface
- PyDev, SWT-based user interface (for Eclipse)
- IEP (Interactive Editor for Pyhton), interactive editor
- Canopy in Enthought: based on PYQT
- Anaconda release of the Spyder in Continuum Analytics: PYQT-based
Iv. Interactive Visualization software package
- D3.js
- Bokeh
- Vispy
- Wakari
- Ashiba
V. Statistics and data Mining algorithms
-
hmm-Hidden Markov model
-
viterbi-Viterbi algorithm
-
Logistic regression
-
Decision Tree: ID3, C4.5, CART---classification
-
K-means (k-means)---clustering algorithm
-
SVM Support Vector Machine---supervised learning, statistical classification and regression analysis
-
Maximum expectation (EM) algorithm
-
PageRank
-
AdaBoost
-
KNN (k-Neighbor algorithm)
-
Bayesian classifier, naive Bayesian
-
Random Forest
-
LDA Thematic model
Vi. Deep Learning
- CNN convolutional Neural Network
- RNN Cyclic Neural network
Python data visualization, data mining, machine learning, deep learning common libraries, IDES, etc.