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Showing posts with label machine learning. Show all posts
Showing posts with label machine learning. Show all posts
Thursday, August 5, 2021

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

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

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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

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Sunday, July 25, 2021

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

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  Case 01 : Ascertaining a positive match using "\w" to match a specific phone number to a generic string Case 02 : Ascertaining a...

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

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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

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

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

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

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

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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

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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

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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

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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

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Thursday, July 22, 2021

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

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  Example - 01 : Joining Numeric List Elements with char string Example - 02 : Joining Tuples with character string Example - 03 : Joining L...
Wednesday, July 21, 2021

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

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Tuesday, July 20, 2021

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

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Monday, July 19, 2021

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

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Sunday, July 18, 2021

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

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

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