March 2021
Beginner to intermediate
261 pages
4h 7m
English
book
Data Science Revealed: With Feature Engineering, Data Visualization, Pipeline Development, and Hyperparameter Tuning
by Tshepo Chris Nokeri
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Index
A
Activation function
loss
ReLu
sigmoid
tanh
Actual values
Adam optimization method
Agglomerative model
clusters
definition
dendogram
distancing techniques
predicted labels
Akaike information criterion (AIC)
Analysis of covariance (ANOVA)
Area under the curve (AUC)
Artificial neural networks
Augmented Dick-Fuller (ADF) test
Autocorrelation function
AutoML
leaderboard
prediction
Autoregressive (AR)
Autoregressive conditionally heteroscedasticity (ARCH) model
Autoregressive integrated moving averages (ARIMA) model
Average precision score (APS)
B
Back propagation
Box plot
C
Censored data
Centroid clustering
Cluster analysis
dataset
definition
Confidence interval (CI)
Correlation coefficients
Correlation matrix
Correlation method
covariance
create x and y array
Eigen matrix
Kendall
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.