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Python For Machine Learning

PythonForMachineLearning

Data Preprocessing in Machine Learning| Linear Regression | Logistic Regression | Confusion Matrix | Trees and Forests

Chapter 1
1.0 Create, Describe Dataframe | Operations with Pandas Dataset
1.1 Navigate Pandas Dataframe rows and columns based on Conditions
1.2 How to add Columns in Pandas DataFrame using INSERT method
1.3 Select records from Pandas Dataframe based on Conditions
1.4 Reading Different file like csv, excel, text, json, zip file through python pandas
1.5 Read Tables from HTML page using Python Pandas
1.6 Map External Values to Pandas Column using map function
1.7 Zip Lists to build Dataframe from scratch
1.8 Search the values of a column in another column in any row
1.9 Use of python dictionary for mapping the values of a column
1.10 Python Pandas Map Function | What if key is missing from the dictionary that we are trying to map?
1.11 Ranking Rows of a Pandas Dataset
1.12 Pandas String Manipulations | String Strip using Python Pandas
1.13 Sort Pandas Dataframe | Sorting in Python Pandas Dataframe

Chapter 2
Work in Progress

Chapter 3
3.0 Replace cell value, Rename a column name of Pandas dataframe
3.1 Select across Multiple Columns of a Python Pandas dataset
3.2 Rename multiple columns of a Pandas Dataset in a single shot
3.3 Python Pandas Brackets Notation Vs Dot Notation
3.4 How to compare columns in pandas | Compare Columns using Dot Notation

Chapter 4
4.0 Apply Built-in functions on the pandas Dataframe | Sum | Max | Min | Count
4.1 Python Pandas Lambda Function | How to apply Pandas Lambda Function to your Dataset
4.2 Pandas any() and all() function

Chapter 5
5.1 Drop Rows and Columns of a Pandas Dataset - P1
5.2 Drop Rows and Columns of a Pandas Dataset - P2
5.3 How to drop specific column of a Pandas Dataset

Chapter 6
6.1 Groupby with Pandas | Filter rows using Groupby
6.2 Pandas Groupby based on Timestamp
6.3 Python Pandas Pivot Table and Groupby Functionality







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