Python
Day-wise Python Learning resources from basic concepts to advanced Python applications such as data science and Machine learning. It also includes cheat-sheets, references which are logged daily to accelerate your learning.
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최종 버전 다운로드 (.zip)- launch.json
- tasks.json
- mod.cpython-36.pyc
- 1_Dice_Roll_Simulator.py
- 2_Guess_The_Number.py
- 3_Hangman.py
- 4_Calculator_GUI.py
- 5_Chat_System_On_Socket_Programming.py
- 6_Diagonal_Difference.py
- 7_Staircase.py
- 8_Time_Conversion.py
- readme.md
- Python_3_Tips.jpg
- coordinates1.csv
- coordinates2.csv
- example.csv
- GetHREF.py
- picture.jpg
- RequestWithHeader.txt
- 01_Print_Function.py
- 02_Comment.py
- 03_Math.py
- 04_Variables.py
- 05_While_Loop.py
- 06_For_Loop.py
- 07_If_Else.py
- 08_Function.py
- 09_Global_Local_Variable.py
- 10_Install_Modules.py
- 11_Import_modules.py
- 12_Write_Append_Read_File.py
- 13_Class.py
- 14_User_Input.py
- 15_Statistics_Module.py
- 16_Tuples_List.py
- 17_Using_WebBrowser.py
- 18_MultiDimensional_List.py
- 19_Reading_CSV.py
- 20_Try_Except.py
- 21_Multiline_print.py
- 22_Dictionaries.py
- 23_Builtin_Functions.py
- 24_OS_Module.py
- 25_SYS_Module.py
- 26_URLLIB_Module_Basic.py
- 27_URLLIB_Module_Custom_Headers.py
- 28_URLLIB_Module_with_JSON.py
- 29_Regular_Expressions.py
- 30_List_Comprehensions.py
- 31_String_Manipulations.py
- 32_Parsing_Websites.py
- 33_TKINTER_Module.py
- 34_TKINTER_Add_Menu.py
- 35_Threading_Module.py
- 36_Threading_Advanced.py
- 37_CX_Freeze_and_Making_Exes.py
- 38_MatPlotLib_Module.py
- 39_Sockets_Programming.py
- 40_Multithreaded_Port_Scanner.py
- 41_Listen_And_Bind_Ports.py
- 42_Client_Server_Systems_With_Sockets.py
- debug.log
- test.py
- Untitled-checkpoint.ipynb
- Python Crash Course Exercises - Solutions-checkpoint.ipynb
- Python Crash Course Exercises -checkpoint.ipynb
- Python Crash Course Exercises - Solutions.ipynb
- Python Crash Course Exercises .ipynb
- Python Crash Course.ipynb
- 1-NumPy-Arrays-checkpoint.ipynb
- 2-Numpy-Indexing-and-Selection-checkpoint.ipynb
- 3-Numpy-Operations-checkpoint.ipynb
- Numpy Exercise - Solutions-checkpoint.ipynb
- Numpy Exercises-checkpoint.ipynb
- 1-NumPy-Arrays.ipynb
- 2-Numpy-Indexing-and-Selection.ipynb
- 3-Numpy-Operations.ipynb
- Numpy Exercise - Solutions.ipynb
- Numpy Exercises.ipynb
- 01-Introduction-to-Pandas-checkpoint.ipynb
- 02-Series-checkpoint.ipynb
- 03-DataFrames-checkpoint.ipynb
- 04-Missing-Data-checkpoint.ipynb
- 05-Groupby-checkpoint.ipynb
- 06-Merging-Joining-and-Concatenating-checkpoint.ipynb
- 07-Operations-checkpoint.ipynb
- 08-Data-Input-and-Output-checkpoint.ipynb
- Pandas Exercise SOLUTIONS-checkpoint.ipynb
- Pandas Exercises-checkpoint.ipynb
- banklist.csv
- Pandas Exercise SOLUTIONS.ipynb
- Pandas Exercises.ipynb
- 01-Introduction-to-Pandas.ipynb
- 02-Series.ipynb
- 03-DataFrames.ipynb
- 04-Missing-Data.ipynb
- 05-Groupby.ipynb
- 06-Merging-Joining-and-Concatenating.ipynb
- 07-Operations.ipynb
- 08-Data-Input-and-Output.ipynb
- example
- Excel_Sample.xlsx
- multi_index_example
- (Optional-No Video) - Advanced Matplotlib Concepts-checkpoint.ipynb
- Matplotlib Concepts Lecture-checkpoint.ipynb
- Matplotlib Exercises - Solutions-checkpoint.ipynb
- Matplotlib Exercises -checkpoint.ipynb
- (Optional-No Video) - Advanced Matplotlib Concepts.ipynb
- filename.png
- Matplotlib Concepts Lecture.ipynb
- Matplotlib Exercises - Solutions.ipynb
- Matplotlib Exercises .ipynb
- Pandas Built-in Data Visualization-checkpoint.ipynb
- Pandas Data Visualization Exercise - Solutions-checkpoint.ipynb
- Pandas Data Visualization Exercise -checkpoint.ipynb
- Visualizing Time Series Data-checkpoint.ipynb
- df1
- df2
- df3
- mcdonalds.csv
- Pandas Built-in Data Visualization.ipynb
- Pandas Data Visualization Exercise - Solutions.ipynb
- Pandas Data Visualization Exercise .ipynb
- Visualizing Time Series Data.ipynb
- Datetime Index-checkpoint.ipynb
- Rolling and Expanding-checkpoint.ipynb
- Time Resampling-checkpoint.ipynb
- Time Shifting-checkpoint.ipynb
- walmart_stock.csv
- Datetime Index.ipynb
- Rolling and Expanding.ipynb
- Time Resampling.ipynb
- Time Shifting.ipynb
- 1-Pandas-Datareader-checkpoint.ipynb
- 2-Quandl-checkpoint.ipynb
- 1-Pandas-Datareader.ipynb
- 2-Quandl.ipynb
- Stock Market Analysis Project SOLUTIONS-checkpoint.ipynb
- Stock Market Analysis Project-checkpoint.ipynb
- Ford_Stock.csv
- GM_Stock.csv
- Stock Market Analysis Project SOLUTIONS.ipynb
- Stock Market Analysis Project.ipynb
- Tesla_Stock.csv
- 1-Introduction-to-Statsmodels-checkpoint.ipynb
- 2-EWMA-Exponentially-weighted-moving-average-checkpoint.ipynb
- 3-ETS-Decomposition-checkpoint.ipynb
- 4-ARIMA-and-Seasonal-ARIMA-checkpoint.ipynb
- 1-Introduction-to-Statsmodels.ipynb
- 2-EWMA-Exponentially-weighted-moving-average.ipynb
- 3-ETS-Decomposition.ipynb
- 4-ARIMA-and-Seasonal-ARIMA.ipynb
- airline_passengers.csv
- monthly-milk-production-pounds-p.csv
- 01-Portfolio-Allocation-and-Sharpe-Ratio-checkpoint.ipynb
- 02-Portfolio-Optimization-checkpoint.ipynb
- 03-CAPM-Capital-Asset-Pricing-Model-checkpoint.ipynb
- 01-Portfolio-Allocation-and-Sharpe-Ratio.ipynb
- 02-Portfolio-Optimization.ipynb
- 03-CAPM-Capital-Asset-Pricing-Model.ipynb
- AAPL_CLOSE
- AMZN_CLOSE
- CISCO_CLOSE
- GOOG_CLOSE
- IBM_CLOSE
- walmart_stock.csv
- 02-Basic-Algorithm-Methods-checkpoint.ipynb
- 03-First-Trading-Algorithm-checkpoint.ipynb
- 04-Trading-Algorithm-Exercise-checkpoint.ipynb
- 05-Trading-Algorithm-Exercise-Solutions-checkpoint.ipynb
- 06-Pipelines-checkpoint.ipynb
- 01-Quantopian-Research-Basics.ipynb
- 02-Basic-Algorithm-Methods.ipynb
- 03-First-Trading-Algorithm.ipynb
- 04-Trading-Algorithm-Exercise.ipynb
- 05-Trading-Algorithm-Exercise-Solutions.ipynb
- 06-Pipelines.ipynb
- 00-Pipeline-Example-checkpoint.ipynb
- 00-Pipeline-Example-Walkthrough-checkpoint.ipynb
- 01-Leverage-checkpoint.ipynb
- 03-Portfolio-Analysis-with-Pyfolio-checkpoint.ipynb
- 04-Stock-Sentiment-Analysis-Project-checkpoint.ipynb
- 05-Futures-checkpoint.ipynb
- 06-Trading-Futures-Example-checkpoint.ipynb
- 00-Pipeline-Example-Walkthrough.ipynb
- 01-Leverage.ipynb
- 02-Hedging.ipynb
- 03-Portfolio-Analysis-with-Pyfolio.ipynb
- 04-Stock-Sentiment-Analysis-Project.ipynb
- 05-Futures.ipynb
- environment.yml
- maclinuxenvironment.yml
- Pierian_Data_Logo.png
- README.md
- Untitled.ipynb
- create_sentiment_featuresets.cpython-36.pyc
- Create_Sentiments_feature_Set.cpython-36.pyc
- 01_Twitter.py
- Basic_Algebra.pdf
- Python_For_DataScience.jpg_large
- R_and_Python_DataScience.jpg
- Bilogical_Neuron_and_Artificial_Neuron.jpg
- breast-cancer-wisconsin.txt
- Epoch.jpg
- Euclidean_Distance.jpg
- Intro to Regression.pdf
- linearregression.pickle
- negetive.txt
- positive.txt
- StockPrediction.png
- titanic.xls
- 01_Pandas_Module.py
- 02_Sklearn_and_Quandl_module.py
- 03_Regression_Train_Test_Predict.py
- 04_Best_Fit_Line_and_Regression.py
- 05_Classification_with_SKLEARN_K_Nearest_Neighbor_Algorithm.py
- 06_KNN_Algorithm_using_Python.py
- 07_Test_Accuracy_of_kNN_Classifier_on_Cancer_Data.py
- 08_Classification_with_SKLEARN_Support_Vector_Machine_Algorithm.py
- 09_Creating_a_SVM_from_scratch.py
- 10_Soft_Margin_SVM_and_Kernels_with_CVXOPT.py
- 11_Clustering_DataSets_with_KMeans_Algorithm.py
- 12_KMeans_on_Titanic_DataSet.py
- 13_Creating_KMeans_from_scratch.py
- 14_Custom_KMeans_Algorithm_on_Titanic_dataset.py
- 15_Mean_Shift_Algorithm_on_Titanic_DataSet.py
- 16_Creaing _MeanShift_Algorithm_from_Scratch.py
- 17_Custom_MeanShift_Algorithm_with_Dynamic_Bandwith.py
- 18_Installing_TensorFlow_on_Windows.py
- 19_TensorFlow_Basic_Example.py
- 20_Neural_Network_with_TensorFlow_on_MNIST_data.py
- 21_Deep_Learning_Neural_Network_and_Sentiment_Analysis.py
- create_sentiment_featuresets.py
- 01_Selenium_With_Python.py
- test.py
- 01_Using_URLLIB_and_REGEX.py
- 02_Using_Beautiful_Soup.py
- 03.py
- 04_PRAW.py
- AutoPost.py
- geckodriver.log
- README.md
// repository documentation
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