GitHub - porom004/Data-Science-Learning-Material: This is github repositories for all data science material I feel important. I would update it daily.

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
13_way_to_see_correlation.pdf		13_way_to_see_correlation.pdf
A tutorial on PCA.pdf		A tutorial on PCA.pdf
Abdi-KendallCorrelation2007-pretty.pdf		Abdi-KendallCorrelation2007-pretty.pdf
Abdi-MCA2007-pretty.pdf		Abdi-MCA2007-pretty.pdf
Advanced Analytics with Spark, 2nd Edition.pdf		Advanced Analytics with Spark, 2nd Edition.pdf
Artificial_network_for_dummies.pdf		Artificial_network_for_dummies.pdf
Azure_ML_cheatsheet.pdf		Azure_ML_cheatsheet.pdf
Big data for dummies.pdf		Big data for dummies.pdf
Big_Data_Principles_and_Best_Practices_of_Scalable_Realtime_Data_Systems_Nathan_Marz _James_Warren.pdf		Big_Data_Principles_and_Best_Practices_of_Scalable_Realtime_Data_Systems_Nathan_Marz _James_Warren.pdf
Confidence_Intervals_for_the_Difference_Between_Two_Means.pdf		Confidence_Intervals_for_the_Difference_Between_Two_Means.pdf
Customer-Propensity-Models-Explained.pdf		Customer-Propensity-Models-Explained.pdf
Data-Transformations-1.pdf		Data-Transformations-1.pdf
Data_fallacies.pdf		Data_fallacies.pdf
Deep Learning Cookbook_ Practic - Douwe Osinga.pdf		Deep Learning Cookbook_ Practic - Douwe Osinga.pdf
Fourier_analysis.pdf		Fourier_analysis.pdf
Hands-On-Machine-Learning-1st.pdf		Hands-On-Machine-Learning-1st.pdf
Hierarchical clustering 2020.pdf		Hierarchical clustering 2020.pdf
Intelligent Projects Using Python 1st Edition.Pdf		Intelligent Projects Using Python 1st Edition.Pdf
JaynesProbabilityTheory.pdf		JaynesProbabilityTheory.pdf
K R Murphy, B Myors - Statistical Power Analysis.pdf		K R Murphy, B Myors - Statistical Power Analysis.pdf
Kernel_density_estimation.pdf		Kernel_density_estimation.pdf
LinRegExp.doc		LinRegExp.doc
Local_outlier_factor.pdf		Local_outlier_factor.pdf
MCA with R.pdf		MCA with R.pdf
Mathematic_for_machine_learning.pdf		Mathematic_for_machine_learning.pdf
Mathematical_cheat_sheet.pdf		Mathematical_cheat_sheet.pdf
Multiple_Factor_Analysis.pdf		Multiple_Factor_Analysis.pdf
Normality_Testing.pdf		Normality_Testing.pdf
Outlier Detection 1.pdf		Outlier Detection 1.pdf
Pandas_Cheat_Sheet.pdf		Pandas_Cheat_Sheet.pdf
Python for Data Analysis.pdf		Python for Data Analysis.pdf
SMOTE.pdf		SMOTE.pdf
Simple_linear_regression.pdf		Simple_linear_regression.pdf
Singular_Value_Decomposition_Tutorial.pdf		Singular_Value_Decomposition_Tutorial.pdf
Statistical_machine_learning.pdf		Statistical_machine_learning.pdf
The_element_of_statistical_learning.pdf		The_element_of_statistical_learning.pdf
Theory_of_correspondence analysis.pdf		Theory_of_correspondence analysis.pdf
Top_deep_learning_interview_question.pdf		Top_deep_learning_interview_question.pdf
UnitRoot_ADF.pdf		UnitRoot_ADF.pdf
[Chollet]-Deep_Learning_with_Python.pdf		[Chollet]-Deep_Learning_with_Python.pdf
alghoritm_selection.png		alghoritm_selection.png
anova.pdf		anova.pdf
artificial-intelligence-modern-approach.9780131038059.25368.pdf		artificial-intelligence-modern-approach.9780131038059.25368.pdf
bootstrap.pdf		bootstrap.pdf
bootstrap_lecture.pdf		bootstrap_lecture.pdf
categorical_encoder_cheat_sheet.png		categorical_encoder_cheat_sheet.png
choosing-a-good-chart-09.pdf		choosing-a-good-chart-09.pdf
classify_multivariate_outlier.pdf		classify_multivariate_outlier.pdf
cluster_unsupervised_learning.jfif		cluster_unsupervised_learning.jfif
comparison_of_classification_alghoritm.pdf		comparison_of_classification_alghoritm.pdf
data-science-from-scratch.pdf		data-science-from-scratch.pdf
data_case_study_collection.pdf		data_case_study_collection.pdf
data_collection.pdf		data_collection.pdf
datascienceinterviewquestion.pdf		datascienceinterviewquestion.pdf
decision_tree_regressor.pdf		decision_tree_regressor.pdf
deep-learning-nlp-speech-recognition.pdf		deep-learning-nlp-speech-recognition.pdf
deep_learning_[Ian_Goodfellow,_Yoshua_Bengio_and_Aaron_Courville(z-lib.org).pdf		deep_learning_[Ian_Goodfellow,_Yoshua_Bengio_and_Aaron_Courville(z-lib.org).pdf
deep_learning_notes.pdf		deep_learning_notes.pdf
detecting_outlier_PyOD.pdf		detecting_outlier_PyOD.pdf
download.png		download.png
effective_way_to_data_collecting.pdf		effective_way_to_data_collecting.pdf
evaluating_model.pdf		evaluating_model.pdf
feature_engineering.pdf		feature_engineering.pdf
feature_selection_technique.pdf		feature_selection_technique.pdf
few_things_to_know_about_machine_learning.pdf		few_things_to_know_about_machine_learning.pdf
few_useful_thing_about_ml.pdf		few_useful_thing_about_ml.pdf
finding_structure_with_randomness.pdf		finding_structure_with_randomness.pdf
greedy_function_approximation.pdf		greedy_function_approximation.pdf
guide_to_data_collection.pdf		guide_to_data_collection.pdf
how_to_detect_multivariate_outlier.pdf		how_to_detect_multivariate_outlier.pdf
how_to_present.jfif		how_to_present.jfif
illustrative_example_propensity.pdf		illustrative_example_propensity.pdf
intro_to_MCMC.pdf		intro_to_MCMC.pdf
intro_to_deep_learning.pdf		intro_to_deep_learning.pdf
linear_classifier.pdf		linear_classifier.pdf
list_of_time_series_method.jfif		list_of_time_series_method.jfif
log_models_intepertation.pdf		log_models_intepertation.pdf
logmodels2.pdf		logmodels2.pdf
maachine_learning_roadmap_anthr.jfif		maachine_learning_roadmap_anthr.jfif
machine_learning_alghoritms.jfif		machine_learning_alghoritms.jfif
machine_learning_implementation.pdf		machine_learning_implementation.pdf
machine_learning_interpretable.pdf		machine_learning_interpretable.pdf
machine_learning_roadmapjfif.jfif		machine_learning_roadmapjfif.jfif
major_types_machine_learning.pdf		major_types_machine_learning.pdf
math_to_machine_learning.pdf		math_to_machine_learning.pdf
missing_data_type.pdf		missing_data_type.pdf
neural_network.jfif		neural_network.jfif
non_parametric_slide.pdf		non_parametric_slide.pdf
outlier_detection.pdf		outlier_detection.pdf
outlier_detection_1.pdf		outlier_detection_1.pdf
outlier_detection_slide.pdf		outlier_detection_slide.pdf
pca.pdf		pca.pdf
python_interview_question.pdf		python_interview_question.pdf
robust_correlation_analysis.pdf		robust_correlation_analysis.pdf
robust_outlier_detection.pdf		robust_outlier_detection.pdf
sql_cheatsheet.pdf		sql_cheatsheet.pdf
sql_join.jfif		sql_join.jfif
statistic_cheat_sheet.pdf		statistic_cheat_sheet.pdf
statistical models - diagram.pdf		statistical models - diagram.pdf
statistics for machine learning.pdf		statistics for machine learning.pdf

About

This is github repositories for all data science material I feel important. I would update it daily.

Activity

0 stars

0 watching

63 forks

Report repository

Releases

No releases published

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

About

Uh oh!

Releases

Packages

Uh oh!

Contributors

Uh oh!

Folders and files

Latest commit

History

About

Uh oh!

Stars

Watchers

Forks

Releases

Packages 0

Uh oh!

Contributors

Uh oh!

Packages