Index
A
B
C
D
- data
- preprocessing / Preprocessing the data
- scaling, to standard normal / Scaling data to the standard normal, How it works...
- line, fitting through / Fitting a line through data, How to do it..., How it works...
- clustering, KMeans used / Getting ready, How to do it…, How it works...
- handling, MiniBatch KMeans used / How to do it..., How it works...
- classifying, with Support Vector Machines (SVM) / Getting ready, How it works…
- exploring / Exploring the data
- data array / Datasets
- DataFrame / Feature extraction
- Dataframe.describe() method / Exploring the data
- data imputation
- data preprocessing
- data set
- dataset
- datasets
- datasets module
- data standardization
- decision boundary / How it works…
- decision tree, versus random forest
- Decision Tree model
- decision trees
- Decision Trees
- decomposition
- dictionary
- DictionaryLearning
- DictVectorizer class / Extracting features from categorical variables
- DictVectorizer option / DictVectorizer
- digit class / Principal Component Analysis
- dimensionality
- dimensionality reduction
- dimensionality reduction
- distance functions
- document classification
- documents
- dual form
- dummy estimators
- dunder / There's more...
E
F
G
- Gauss-Markov theorem
- Gaussian distribution
- Gaussian kernel
- Gaussian Mixture Models
- Gaussian Mixture Models (GMM)
- Gaussian process
- GaussianProcess object
- Gaussian process object
- gaussian_process module
- geometric margin
- Gini impurity / Gini impurity
- gradient boosting regression
- gradient descent
- Graphviz
- greedy / The advantages and disadvantages of decision trees
- grid search
H
I
J
- Jaccard similarity
- joblib
K
L
M
- %matplotlib inline command / Getting sample data from external sources
- Mac
- Scikit-learn, installing on / Mac
- machine learning
- machine learning (ML) / Introduction
- machine learning categories
- margin
- matplotlib
- matplotlib package
- max_depth parameter / How it works..., How to do it…
- mean absolute deviation (MAD)
- mean squared error (MSE)
- measure_performance function / Evaluation
- meshgrid
- MiniBatch KMeans
- missing values
- MLP
- model
- models
- model selection
- multi-class classification
- multi-label classification
- multiclass classification
- MultinomialNB algorithm / Model selection
- multiple linear regression
- multiple preprocessing steps
N
O
P
Q
- QDA
- Quadratic kernels
- questioners / Decision trees
- questions, decision trees
R
S
T
U
V
W
- Windows
- Windows installer
X
Z
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