Introduction To Python Data Structure And Linear Regression

Manipulating and analyzing python data structure in depth and understanding linear regression with associated concepts.

What you'll learn

Like a master chef crafting a signature dish, you'll learn to cook up python data structures from a recipe of brackets and commas.

Delve into the spellbook of linear regression methods, which contain enchantments like `EDA`, `MISSING DATA ANALYSIS `, NORMALIZATION to manipulate data.

Learn the incantations to safely dealing with python data structures and preventing any unintended alterations to your original creations.

Become adept at performing magical operations such as concatenation, multiplication, and comparison to merge, replicate, and linear model in data analytics

Requirements

Python,IDE, Statistics, Machine Learning

Description

Unleash the power of python data structures and in-depth analysis of linear regression with this immersive and exciting video lesson on the Introduction to python data structure and linear regression! The tutorial covers important concepts and functions that are crucial for manipulating and analyzing data efficiently using Python.This Course  has been designed for ease and better clarity to online learners starting from how to work with a python data structure and to  perform regression operations on a data frame.From importing and exporting data to and transforming data, this course covers that are crucial for manipulating and analyzing data . We will dive into the essentials of python data structures and regression by demystifying complex concepts through clear and engaging examples.You will also learn how to perform advanced data operations such as merging, grouping, and aggregating data with ease. Unravel step-by-step examples that'll make even complex concepts a breeze to grasp, unfolding the wonders of advanced python Data structures and regression Techniques.From dazzling videos to interactive explanations, this lesson is perfect for student, professional, or data enthusiast seeking clarity on python Data structures and linear regression.Dive into the world of python Data structures with this comprehensive online tutorial, perfect for beginners looking to enhance their data analysis skills. You will positively gain a solid foundation for further exploration in the field and learn how to handle and analyze data efficiently, andBy the end of this course, you will be able to confidently work with python data frames and tackle complex data analysis tasks like a pro.So grab your pencil, sharpen your focus, and get ready to unlock the secrets of  this course that will equip you with the necessary knowledge to excel in python and data analysis tasks.

Overview

Section 1: Introduction to list

Lecture 1 Introduction

Lecture 2 List Creation

Lecture 3 Python list overview

Lecture 4 List access with tabulation for clarification

Lecture 5 List Access and it's associated operations

Lecture 6 List useful methods and its operations

Lecture 7 List deletion with del keyword and empty list

Lecture 8 List conversion to tuple,set and dictionary

Section 2: Introduction to tuple

Lecture 9 Introduction

Lecture 10 Tuple creation

Lecture 11 Tuple access

Lecture 12 Iterating through a Tuple

Lecture 13 Changing, Reassigning, and Deleting Tuples

Lecture 14 Tuples vs. Lists

Lecture 15 Tuple method with description

Lecture 16 Tuple use case

Lecture 17 Summary

Section 3: Introduction to Set

Lecture 18 Introduction

Lecture 19 Example of set

Lecture 20 Set Operations

Lecture 21 Set Creation

Lecture 22 Set Example

Lecture 23 Frozen Set

Lecture 24 Frozen set with detailed information

Lecture 25 Frozen set usage

Lecture 26 Summary

Section 4: Dictionary

Lecture 27 Introduction

Lecture 28 Dictionary structure and examples

Lecture 29 Accessing Elements

Lecture 30 Accessing elements using get

Lecture 31 Adding and Modifying Entries to a Dictionary

Lecture 32 Removing or Deleting Elements from a Dictionary

Lecture 33 Delete an Dictionary

Lecture 34 Setdefault() method

Lecture 35 Dictionary copy method

Lecture 36 Dictionary fromkeys method

Lecture 37 Dictionary with example and detailed content

Lecture 38 Summary

Section 5: Python libraries for data analysis

Lecture 39 Introduction

Lecture 40 Python libraries widely used for analysis machine learning and statistics

Lecture 41 Importing libraries

Lecture 42 Loading training data

Lecture 43 Loading testing data

Lecture 44 Removing Unnecessary Attributes

Lecture 45 Correlation check

Lecture 46 Multicollinearity

Lecture 47 Outliers detection

Lecture 48 Data Preprocessing

Lecture 49 Delete Unuseful Features

Lecture 50 Fix Datatype

Lecture 51 Check Mising Values

Lecture 52 Imputing missing values

Lecture 53 Feature Engineering

Lecture 54 Numeric Feature Scaling

Lecture 55 Skewing with boxcox_normmax()

Lecture 56 Adding New Features

Lecture 57 Numerical and categorical features

Lecture 58 Encoding Categorical Variables

Lecture 59 One Hot Encoding

Lecture 60 Train and test data set

Lecture 61 Target Variable Analysis

Lecture 62 Target Variable Transformation

Section 6: Modeling

Lecture 63 Cross Validation

Lecture 64 Evaluation Metric

Lecture 65 Linear Models

Whether you're a novice scribe or a seasoned programmer looking to expand your repertoire, this course will have you conjuring lists with the finesse of a Pythonista.