NBA Winning Estimator with Decision Tree in Python

It would be interesting to conduct prediction to understand the trend of NBA winning teams. We will use data from http://www.basketball-reference.com/leagues/NBA_2017_games-june.html and follow workflow. More details can be found in Robert Layton's book here: https://www.goodreads.com/book/show/26019855-learning-data-mining-with-python?from_search=true

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Comparative Visualization of IBM&Google

I want to create an infographic using data provided (related to Google and IBM). To create a comparative visualization, enabling the reader to have an experience with this dataset. When developing an infographic, let the data flush out the concept rather then work up a concept and try to force the chart into an idea… Continue reading Comparative Visualization of IBM&Google

Clustering Application in Face Recognition in Python

We used face datasets for PCA application here: https://charleshsliao.wordpress.com/2017/05/28/preprocess-pca-application-in-python/ It also will be interesting to see how clustering algorithms assign images into different clusters and visualize them. We use the data from sklearn library(need to download face datasets separately), and the IDE is sublime text3. Most of the code comes from the book: https://www.goodreads.com/book/show/32439431-introduction-to-machine-learning-with-python?from_search=true

Multi Layer Perceptrons in Python

You can see more about MLP in R here: https://charleshsliao.wordpress.com/2017/04/10/tune-multi-layer-perceptron-mlp-in-r-with-mnist/ Generally speaking, a deep learning model means a neural network model with more than just one hidden layer. Whether a deep learning model would be successful depends largely on the parameters tuned. We use the data from sklearn library, and the IDE is sublime text3.… Continue reading Multi Layer Perceptrons in Python

Logistic Regression in Python to Tune Parameter C

The trade-off parameter of logistic regression that determines the strength of the regularization is called C, and higher values of C correspond to less regularization (where we can specify the regularization function).C is actually the Inverse of regularization strength(lambda) We use the data from sklearn library, and the IDE is sublime text3. Most of the… Continue reading Logistic Regression in Python to Tune Parameter C