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.
My [day-wise] Python Learning journey
Python 3 Learning
Python language reference
Python cheat sheets
Python quick reference cards
Parsing websites
TKinter module to make windows forms
MINI PROJECT
Mini Project
Euclidean distance
Making your own k-NN (k-Nearest Neighbor) algorithm in python
Comparing the accuracy and confidence of your algorithm with SKLearn module's neighbors.KNeighborsClassifier()
Accuracy vs confidence in k-NN algorithm
.Root
| README.md
|
+---.vscode
| launch.json
| tasks.json
|
+---Python Basics
| | 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
| |
| +---MiniProjects
| | 1_Dice_Roll_Simulator.py
| | 2_Guess_The_Number.py
| | 3_Hangman.py
| | 4_Calculator_GUI.py
| | 5_Chat_System_On_Socket_Programming.py
| | readme.md
| |
| +---Resources
| | Python_3_Tips.jpg
| |
| \---SampleFiles
| coordinates1.csv
| coordinates2.csv
| example.csv
| GetHREF.py
| picture.jpg
| RequestWithHeader.txt
|
+---Python Machine Learning
| | 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
| |
| +---MiniProjects
| | 01_Twitter.py
| |
| +---Resources
| | Basic_Algebra.pdf
| | Python_For_DataScience.jpg_large
| | R_and_Python_DataScience.jpg
| |
| \---SampleFiles
| breast-cancer-wisconsin.txt
| Euclidean_Distance.jpg
| Intro to Regression.pdf
| linearregression.pickle
| StockPrediction.png
| titanic.xls
|
+---Python Selenium
| 01_Selenium_With_Python.py
|
+---Python Web Scraping
| 01_Using_URLLIB_and_REGEX.py
| 02_Using_Beautiful_Soup.py