One Hot Encoding and Dummy Variables Generation upon a dataframe | Scenario - Perform One-Hot Encoding upon Un-Ordered Data in a sample dataframe and generate One-hot encoded feature variables | Conceptual Infographic Note

 

Handling Categorical Data in Dataframe and Dataset | Types of Categorical Data and its examples | Conceptual Infographic Note

 

Label Encoding and Ordinal Encoding in Python | Scenario - Perform Ordinal Encoding upon Ordered Data in a sample dataframe and generate encoded features of the data | Conceptual Infographic Note

 

Regular Expressions in Python | Scenario - Finding sub-string match patterns to validate a genuine number from a numeric string using Regular Expressions and search() method in Python | Conceptual Infographic Note

 

Case 01 : Ascertaining a positive match using "\w" to match a specific phone number to a generic string

Case 02 : Ascertaining a negative  match or mismatch using "\w" whether a  match over given string occurs or not

Regular Expressions in Python | Scenario - Finding a sub-string match and its count from a main string using Regular Expressions and findall() function in Python | Conceptual Infographic Note

 

Regular Expressions in Python | Scenario - Replacing a word ("sub-string") with another word ("sub-string") in a main string using Regular Expressions and substitute function in Python | Conceptual Infographic Note

 

Regular Expressions in Python | Scenario - Finding matching pattern of the main string using Regular Expressions and findall() function in Python | Conceptual Infographic Note

 

Regular Expressions in Python | Scenario - Finding Positional Indexes of each matching pattern of the main string using Regular Expressions | Conceptual Infographic Note

 

Regular Expressions in Python | Scenario - Finding and Retrieving specific sub-strings with commonality in patterns using Regular Expressions | Conceptual Infographic Note

 

Regular Expressions in Python | Scenario - Finding and Retrieving specific sub-strings with commonality in patterns using Regular Expressions | Conceptual Infographic Note

 

Regular Expressions in Python | Scenario - Finding and Retrieving specific sub-string and their cpount of occurrence from a main parent string using regular expressions | Conceptual Infographic Note

 

Regular Expressions in Python | Scenario - Finding and Retrieving specific positional indexes of sub-strings and index positions from a parent string using regular expressions and store them in one dictionary | Conceptual Inforgraphic Note

 

Regular Expressions in Python | Scenario - Finding and Retrieving specific sub-strings and integers from a parent string using regular expressions and store them in one dictionary | Conceptual Inforgraphic Note

 

Regular Expressions in Python usecase Scenario | Finding and Retrieving specific sub-strings from a parent string using regular expressions and storing in separate list | Conceptual Inforgraphic Note

 

Examples of Using "JOIN" function on Python Data Structures | Sample Conceptual Questions with Answers with examples | Infographic Note

 

Example - 01 : Joining Numeric List Elements with char string

Example - 02 : Joining Tuples with character string

Example - 03 : Joining List elements with long string

Example - 04 : Joining Character List Elements with long string

Example - 05 : Joining Character List Elements with null string

StopWords Filtering using NLTK library Conceptual Infographic Notes | Pre-Requisite Concept for Natural Language Processing Projects and Analysis with sample example , code and analysis

 

Stemming Concept for text pre-processing in Natural Language Processing Conceptual Infographic Notes | Stemming Concept with example and explanatory notes

 

Building "HangMan" Game Project in Python | Word Guessing Game from Letters | Infographic Note with Code and Step by Step Explanation

 

Twitter Sentiment Analysis Conceptual Infographic Notes | Getting Started with Sentiment Analysis based NLP Project with its main objectives , considerations , challenges , Approach and Steps

 

Introduction to the concept of "Term Frequency - Inverse Document Frequency (TF-IDF)" with 3 general questions and answers | An Infographic Note

 

More on this at : https://towardsdatascience.com/tf-idf-for-document-ranking-from-scratch-in-python-on-real-world-dataset-796d339a4089