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ai-and-ml ai and ml faq Dec 16, 2016
bagging-boosting-rf bagging vs boosting vs rf Nov 9, 2015
choosing-technique choosing technique Nov 8, 2015
classifier-history classifier-history Nov 8, 2015
classifier_categories master chart Dec 9, 2015
clf-behavior-data What are the best toy datasets to help visualize and understand class… Feb 17, 2016
closed-form-vs-gd consistend indeces May 27, 2016
datascience-ml
decision-tree-binary decision trees Nov 9, 2015
decisiontree-error-vs-entropy adding entropy and error plots Nov 28, 2015
diff-perceptron-adaline-neuralnet diff neural net adaline perceptron.md Mar 20, 2016
difference-deep-and-normal-learning
dimensionality-reduction dimensionaliity reduction Nov 8, 2015
euclidean-distance euclidean distance Nov 9, 2015
evaluate-a-model evaluate in vector graphics Oct 9, 2017
issues-with-clustering consistency in filenames Nov 8, 2015
large-num-features image links Nov 9, 2015
lda-vs-pca lda vs pca Nov 9, 2015
linear-gradient-derivative
logistic-why-sigmoid logistic why sigmoid Mar 20, 2016
logistic_regression_linear faq enhancement logistic generalized linear model Feb 15, 2016
logisticregr-neuralnet logistic regression and neural net faq Dec 1, 2015
median-vs-mean mean vs median Nov 16, 2015
ml-curriculum ml curriculum Nov 12, 2015
ml-examples ml realworld examples Nov 14, 2015
ml-solvable How do I know if the problem is solvable through machine learning? Nov 8, 2015
multiclass-metric multiclass performance metrics Nov 8, 2015
naive-bayes-boundary naive bayes boundary Nov 9, 2015
naive-bayes-vartypes gaussian nb w mixed variables Nov 10, 2015
naive-naive-bayes naive bayes Nov 17, 2015
neuralnet-error faq: What is wrong when my neural network's error increases? Mar 9, 2016
overfitting overfitting faq Dec 19, 2015
pca-scaling pca and scaling Nov 12, 2015
pearson-r-vs-linear-regr more details to the slope eq Nov 17, 2015
probablistic-logistic-regression probablistic interpretation of logistic regression Nov 9, 2015
regularized-logistic-regression-performance update l2 term Jun 24, 2016
select_svm_kernels how to select svm kernels Mar 2, 2016
softmax softmax Nov 9, 2015
softmax_regression
svm_for_categorical_data svm for categorical Nov 13, 2016
tensorflow-vs-scikitlearn What is the main difference between TensorFlow and scikit-learn Mar 19, 2016
visual-backpropagation visual backpropagation Nov 9, 2015
why-python consistency in filenames Nov 8, 2015
README.md avoid overfitting answer Jan 14, 2017
ai-and-ml.md ai and ml faq Dec 16, 2016
avoid-overfitting.md avoid overfitting answer Jan 14, 2017
bag-of-words-sparsity.md bag-of-words-sparsity Mar 19, 2016
bagging-boosting-rf.md Fixed minor typos. Feb 21, 2017
best-ml-algo.md best ml algoo Nov 9, 2015
choosing-technique.md
classifier-categories.md master chart Dec 9, 2015
classifier-history.md classifier-history Nov 8, 2015
clf-behavior-data.md change mlxtend.evaluate references to mlxtend.plotting Apr 30, 2017
closed-form-vs-gd.md closed-form vs. gd vs. sgd Nov 18, 2015
computing-the-f1-score.md passage flip May 4, 2016
copyright.md minor typos. Dec 12, 2016
cost-vs-loss.md
data-science-career.md Update data-science-career.md Nov 11, 2015
datamining-overview.md datamining overview Nov 9, 2015
datamining-vs-ml.md fix typo Jun 21, 2016
dataprep-vs-dataengin.md data preprocessing vs engineering Mar 3, 2016
datascience-ml.md What are machine learning and data science? Feb 12, 2016
decision-tree-binary.md fixing a few links Nov 9, 2015
decision-tree-disadvantages.md decision tree error metric Nov 28, 2015
decisiontree-error-vs-entropy.md add assumption to entropy vs class error in tree splitting Oct 25, 2016
deep-learning-resources.md deep learning resources Nov 8, 2015
deeplearn-vs-svm-randomforest.md faq: How can I know if Deep Learning works better for a specific prob… Feb 14, 2016
deeplearning-criticism.md deep learning criticism Nov 9, 2015
definition_data-science.md remove extra meta data Aug 28, 2016
diff-perceptron-adaline-neuralnet.md change mlxtend.evaluate references to mlxtend.plotting Apr 30, 2017
difference-deep-and-normal-learning.md fix small typo (#64) Oct 14, 2017
difference_classifier_model.md difference model and classifier Dec 10, 2015
different.md small typo Dec 13, 2016
dimensionality-reduction.md
dropout.md dropout technique May 9, 2016
euclidean-distance.md
evaluate-a-model.md How do I evaluate a model? Nov 9, 2015
feature_sele_categories.md difference between filter, wrapper, and embedded methods for feature … Mar 2, 2016
implementing-from-scratch.md fix faq typo Mar 7, 2016
inventing-deeplearning.md deep learning invention Nov 9, 2015
issues-with-clustering.md consistency in filenames Nov 8, 2015
large-num-features.md image links Nov 9, 2015
lazy-knn.md faq: why KNN is *lazy* Feb 10, 2016
lda-vs-pca.md all links ffixed Nov 9, 2015
linear-gradient-derivative.md readibility upd Nov 27, 2015
logistic-analytical.md faq: analytical solution to Logistic Regression similar to the Normal… Feb 21, 2016
logistic-boosting.md faq: What is the difference between a *cost function* and a *loss fun… Feb 21, 2016
logistic-why-sigmoid.md logistic why sigmoid Mar 20, 2016
logistic_regression_linear.md faq enhancement logistic generalized linear model Feb 15, 2016
logisticregr-neuralnet.md
many-deeplearning-libs.md How do I evaluate a model? Nov 9, 2015
median-vs-mean.md mean vs median img Nov 16, 2015
mentor.md opensource and mentor Nov 8, 2015
missing-data.md dealing with missing data Jan 3, 2016
ml-curriculum.md ml curriculum Nov 12, 2015
ml-examples.md mean vs median Nov 16, 2015
ml-origins.md origins of ml Nov 9, 2015
ml-python-communities.md
ml-solvable.md How do I know if the problem is solvable through machine learning? Nov 8, 2015
ml-to-a-programmer.md
model-selection-in-datascience.md
multiclass-metric.md multiclass performance metrics Nov 8, 2015
naive-bayes-boundary.md naive bayes boundary Nov 9, 2015
naive-bayes-vartypes.md
naive-bayes-vs-logistic-regression.md naive bayes vs logreg Nov 9, 2015
naive-naive-bayes.md
neuralnet-error.md
nnet-debugging-checklist.md add to neuralnet debugging checklist Mar 19, 2016
num-support-vectors.md explaining ml Nov 12, 2015
number-of-kfolds.md size of k and variance Nov 9, 2015
open-source.md open source Nov 9, 2015
overfitting.md overfitting faq Dec 19, 2015
parametric_vs_nonparametric.md parametric vs. nonparametric Jan 29, 2016
pca-scaling.md typo fix Nov 13, 2015
pearson-r-vs-linear-regr.md more details to the slope eq Nov 17, 2015
prerequisites.md FAQ Are There Any Prerequisites and Are There Any Pre-Readings? Sep 30, 2015
probablistic-logistic-regression.md probablistic interpretation of logistic regression Nov 9, 2015
py2py3.md some typo fixes Sep 21, 2015
r-in-datascience.md faq: Is R used extensively today in data science? Feb 14, 2016
random-forest-perform-terribly.md When can a random forest perform terribly? Feb 14, 2016
regularized-logistic-regression-performance.md fix merge conflicts Jun 26, 2016
return_self_idiom.md the puprose of the `return self` idioms in my code examples Mar 3, 2016
scale-training-test.md add linebreaks for clarity Feb 10, 2016
select_svm_kernels.md how to select svm kernels Mar 2, 2016
semi-vs-supervised.md update semisupervised Jul 29, 2016
softmax.md softmax Nov 9, 2015
softmax_regression.md What is Softmax regression and how is it related to Logistic regression? Feb 13, 2016
standardize-param-reuse.md typo fixes Nov 8, 2015
svm_for_categorical_data.md svm for categorical Nov 13, 2016
technologies.md some typo fixes Sep 21, 2015
tensorflow-vs-scikitlearn.md note about tf_classifier Jul 22, 2018
underscore-convention.md Missing word (have) and typos Apr 1, 2017
version.md some typo fixes Sep 21, 2015
visual-backpropagation.md visual backpropagation Nov 9, 2015
when-to-standardize.md standardization Nov 9, 2015
why-python.md fixed broken link to why-python post May 13, 2016

README.md

Python Machine Learning FAQ

It is always a pleasure to engage in discussions all around machine learning and I am happy to answer any questions regarding this book.

I just thought that it might be worthwhile to compile some documents about the most commonly asked questions to answer them more thoroughly.

Just drop me your question, feedback, or suggestion via your medium of choice and it will be answered :)

Cheers, Sebastian

FAQ

General Questions about Machine Learning and 'Data Science'

Questions about the Machine Learning Field

Questions about Machine Learning Concepts and Statistics

Cost Functions and Optimization
Regression Analysis
Tree models
Model evaluation
Logistic Regression
Neural Networks and Deep Learning
Other Algorithms for Supervised Learning
Unsupervised Learning
Semi-Supervised Learning
Ensemble Methods
Preprocessing, Feature Selection and Extraction
Naive Bayes
Other
Programming Languages and Libraries for Data Science and Machine Learning



Questions about the Book