GitHub - qingkaikong/blog: Contain all the stuff in my blog

This repo will contains Qingkai's blog entries. You can find Qingkai's blog here.

Name		Name	Last commit message	Last commit date
Latest commit History 456 Commits
01_An_example_of_Bayesian_Analysis_with_python		01_An_example_of_Bayesian_Analysis_with_python
02_Different_priors		02_Different_priors
03_Subspace_detector		03_Subspace_detector
04_Empirical_Subspace_detector		04_Empirical_Subspace_detector
05_top_10_algorithms_in_20c		05_top_10_algorithms_in_20c
06_setup_hadoop_using_sandbox		06_setup_hadoop_using_sandbox
07_MCMC_Regression		07_MCMC_Regression
08_profile_python		08_profile_python
09_query_USGS_and_plot		09_query_USGS_and_plot
10_plot_heatmap_on_Basemap		10_plot_heatmap_on_Basemap
11_shift_signal_in_frequency_domain		11_shift_signal_in_frequency_domain
12_mining_Gmail		12_mining_Gmail
13_profile_f2py		13_profile_f2py
14_plot_histogram_on_clock		14_plot_histogram_on_clock
15_plot_historical_moment_tensors		15_plot_historical_moment_tensors
16_tqdm_progress_bar		16_tqdm_progress_bar
17_folium_map_1_different_map_tiles		17_folium_map_1_different_map_tiles
18_folium_map_2_custom_icon		18_folium_map_2_custom_icon
19_folium_map_3_heatmap		19_folium_map_3_heatmap
2017_01_detect_periodic_signal		2017_01_detect_periodic_signal
2017_02_intuitive_autocorrelation		2017_02_intuitive_autocorrelation
2017_03_paintings_from_my_wife		2017_03_paintings_from_my_wife
2017_04_Entrepreneurship_bootcamp		2017_04_Entrepreneurship_bootcamp
2017_05_More_on_applying_ANN		2017_05_More_on_applying_ANN
2017_06_Mermaid_transformation		2017_06_Mermaid_transformation
2017_07_Pager_duty		2017_07_Pager_duty
2017_08_Cubism_paintings		2017_08_Cubism_paintings
2017_09_enable_GPU_on_macbook_pro_for_deeplearning		2017_09_enable_GPU_on_macbook_pro_for_deeplearning
2017_11_Tar_sands		2017_11_Tar_sands
2017_12_machine_learning_funny_pictures		2017_12_machine_learning_funny_pictures
2017_13_visualize_high_dimensional_dataset		2017_13_visualize_high_dimensional_dataset
2017_14_nice_python_features		2017_14_nice_python_features
2017_15_using_virtualenv		2017_15_using_virtualenv
2017_16_new_baby		2017_16_new_baby
2017_17_scikit-learn-1		2017_17_scikit-learn-1
2017_18_scikit-learn-2		2017_18_scikit-learn-2
2017_19_scikit-learn-3		2017_19_scikit-learn-3
2017_20_scikit-learn-4		2017_20_scikit-learn-4
2017_21_scikit-learn-5		2017_21_scikit-learn-5
2017_22_searching_in_gmail		2017_22_searching_in_gmail
2017_23_EEW		2017_23_EEW
2017_25_FFT_with_different_noise_level		2017_25_FFT_with_different_noise_level
2017_26_Harvard_MIT_BU_visit		2017_26_Harvard_MIT_BU_visit
2017_27_mask_dots_in_water		2017_27_mask_dots_in_water
2017_28_T-shirt-competition		2017_28_T-shirt-competition
2017_29_grab_data_from_website		2017_29_grab_data_from_website
2017_31_discrete_colormap_matplotlib		2017_31_discrete_colormap_matplotlib
2017_32_kdtree		2017_32_kdtree
2017_33_kdtree_2_real_distance		2017_33_kdtree_2_real_distance
2018_01_QGIS_projection_systems		2018_01_QGIS_projection_systems
2018_02_QGIS_style		2018_02_QGIS_style
2018_03_arcgis_online		2018_03_arcgis_online
2018_04_SHM_smartphone		2018_04_SHM_smartphone
2018_05_nice_sayings		2018_05_nice_sayings
2018_06_Santa_Fe		2018_06_Santa_Fe
2018_07_Eugene		2018_07_Eugene
2018_18_Curve_fitting		2018_18_Curve_fitting
2018_19_pandas_groupby		2018_19_pandas_groupby
2018_20_jenkspy		2018_20_jenkspy
2018_21_interactive_plot_with_plotly		2018_21_interactive_plot_with_plotly
2018_22_debugging_in_notebook		2018_22_debugging_in_notebook
2018_23_Maker_Faire		2018_23_Maker_Faire
2018_24_new_office		2018_24_new_office
2018_25_kernel_density_estimation		2018_25_kernel_density_estimation
2018_26_classes_in_python		2018_26_classes_in_python
2018_27_Turle_graphics		2018_27_Turle_graphics
2018_28_ICA		2018_28_ICA
2018_29_profiler_in_jupyter		2018_29_profiler_in_jupyter
2018_30_gas_gain		2018_30_gas_gain
2018_31_finding_peaks		2018_31_finding_peaks
2018_32_create_kml_for_MT		2018_32_create_kml_for_MT
2018_33_the_date_we_use/data		2018_33_the_date_we_use/data
2018_34_google_map_cluster		2018_34_google_map_cluster
2018_36_my_first_NSF_proposal		2018_36_my_first_NSF_proposal
2018_37_Julia_1pt0		2018_37_Julia_1pt0
2018_38_Pandas_dataframe_slicing_milliseconds		2018_38_Pandas_dataframe_slicing_milliseconds
2018_39_spell_check_in_Jupyter_notebook		2018_39_spell_check_in_Jupyter_notebook
20_python_basemap_background		20_python_basemap_background
21_folium_map_4_draw_lines		21_folium_map_4_draw_lines
22_joblib		22_joblib
23_folium_map_5_overlay_image		23_folium_map_5_overlay_image
24_folium_map_6_layer_control		24_folium_map_6_layer_control
25_Pelican_create_personal_website_part1		25_Pelican_create_personal_website_part1
26_Pelican_create_personal_website_part2		26_Pelican_create_personal_website_part2
27_git_contribute_open_source_project		27_git_contribute_open_source_project
28_DBSCAN		28_DBSCAN
29_Processing_InSAR_Sentinel		29_Processing_InSAR_Sentinel
30_PyData		30_PyData
31_data_science_20_questions		31_data_science_20_questions
32_datashader		32_datashader
33_ML_explained_1_What_is_machine_learning		33_ML_explained_1_What_is_machine_learning
34_ML_explained_2_Types_of_ML		34_ML_explained_2_Types_of_ML
35_why_do_we_need_taper		35_why_do_we_need_taper
36_cross-correlation_time_and_frequency_domain		36_cross-correlation_time_and_frequency_domain
37_Caltech_test		37_Caltech_test
38_ANN_part1		38_ANN_part1
39_ANN_part2_step_by_step		39_ANN_part2_step_by_step
40_ANN_part3_step_by_step_MLP		40_ANN_part3_step_by_step_MLP
41_ANN_part4_handwriting_classification		41_ANN_part4_handwriting_classification
42_parallel_method_in_class		42_parallel_method_in_class

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