AI ( Artificial intelligence )

Section 1. Introduction

Section 2. Data Science and Machine Learning

Section 3. AI Project Life Cycle

Section 4. Python the Most Powerful Language

Section 5. Python the Most Powerful Language Part 02

Section 6. Python the Most Powerful Language Part 03

Section 7. Python the Most Powerful Language Part 04

Creating Lists Programmatically

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AND OR Keywords

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If Else Statement

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Intro to Process of Coding Conditionals

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Sets Data Types

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Tuple Data Types

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Most Used Methods on Dictionaries

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Dictionary Key is Unchangeable

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Dictionary

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Boolean Result of Different Values

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Section 8. Python the Most Powerful Language Part 05

Section 9. Python Part-2

Functions

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Scope of a Function

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Exercise (Skipped – No Video Link)

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Args and Kwargs

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Good Programming Practices

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Doc String

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Return Keyword

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Default Parameters

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Parameter vs Argument

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Why of Functions

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Scope Rules 1

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Section 10. Python Part-3

Scope Rules 2

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Python Modules

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Sets and Dictionary Comprehension

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List Comprehension Case 1, 2, and 3

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Special Functions Reduce

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Special Functions Zip

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Special Functions Filter

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Special Functions Map

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Programming Best Practices 2

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Global vs Nonlocal Keywords

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Python Packages

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Section 11. Environment Setup for Machine Learning Projects

Who is Mr. Conda

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Loading and Visualizing Data

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Walkthrough of Jupyter Notebook 2

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Walkthrough of Jupyter Notebook 1

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Installing for MacOS and Linux

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Starting Jupyter Notebook

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Installing Tools

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Installing Conda

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Blueprint of Machine Learning Project

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Setting Up Machine Learning Project

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Tools for Data Science Environment

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Summing It Up

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Section 12. Pandas for Data Analysis

Tools Needed

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Add Remove Data

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Changing Data

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Data Selection 2

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Data Selection

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Describing Data

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How to Import Data

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Data Frames

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Pandas and What We Will Cover

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Manipulating Data

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Section 13. NumPy

Section 14. NumPy Part 02

Section 15. Matplotlib

Matplotlib Intro

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Pandas Data Frame

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Four Plots One Figure

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Histogram

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Most Used Plots (Bar Plot)

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One Figure Many Plots

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Setting Up Features

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Methods to Plot

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First Plot with Matplotlib

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Plotting from Pandas Data Frame

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Section 16. Matplotlib Part 02

Section 17. Scikit-Learn

Section 18. Scikit-Learn Part 02

What We Are Going to Do

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Using Map to Choose Model

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Choosing Machine Learning Model

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Getting Data (Missing Values Method 2)

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Getting Data (Missing Values)

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Getting Data (Second Method of Conversion)

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Getting Data (Anatomy of Conversion)

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Getting Data Ready Converting Part 1

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Step 1 Getting Data Split Data

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Step 2 How to Choose Better Model

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Section 19. Scikit-Learn Part 03

Choosing Model for Classification Problem

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Step 4 Area Under the Curve Part 1

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Step 4 Accuracy (Classification Model)

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Step 4 What is Cross Validation

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Step 4 Evaluating Machine Learning Model (Default Scoring)

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Step 3 Running Prediction on Regression Problem

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Step 3 Predict Proba Method

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Running Prediction

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Fit the Model

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Step 4 Area Under the Curve Part 2

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Section 20. Scikit-Learn Part 04

Step 4 Area Under the Curve Part 3 (Plotting)

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Step 4 Evaluation Using Functions (Classification)

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Step 4 Scoring Parameters for Regression

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Step 4 Scoring Parameters for Classification

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Step 4 Mean Square Error for Regression Problems

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Step 4 Mean Absolute Error for Regression Problems

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Step 4 R2 for Regression Problems

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Step 4 Classification Report Fully Explained

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Step 4 Classification Report (Important Concepts)

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Step 4 Confusion Matrix Plot

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Confusion Matrix Calculate

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Step 4 Evaluation Using Functions (Regression)

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Section 21. Scikit-Learn Part 05

Step 5 Improving Model by Hyperparameters

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Step 5 Improving Model by Hyperparameters Manually

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Step 5 Hyperparameters Task 1

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Step 5 Evaluation Metrics in One Function

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Step 5 Hyperparameters Comparison

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Tuning Hyperparameters Using RSCV

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Tuning Hyperparameters Using RSCV Part 2

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Tuning Hyperparameters Using GSCV

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Results Comparison

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Section 22. Scikit-Learn Part 06

Section 23. Project 1 Part 01

Milestone Project 1 Intro

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Chest Pain Type and Target Relation Part 2

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Chest Pain Type and Target Relation Part 1

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Age Distribution

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Scatter Plot to See Any Pattern

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Be Careful with Plot Choice

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Exploratory Data Analysis Part 2

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Exploratory Data Analysis Part 1

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Importing Tools and Libraries

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Data Features Recognition

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First 4 Steps

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Creating Project Environment

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Correlation Matrix Part 1

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Section 24. Project 1 Part 02

Plotting Correlation Matrix Part 2

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Modelling Split the Data

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Choosing the Right Model

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Improving Model

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Plotting the Improved Model Score

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Hyperparameter Tuning Using GSCV

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Hyperparameters for RandomForestClassifier

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Running the Model with Hyperparameters Using GSCV

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Score Comparison After Tuning

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Section 25. Project 1 Part 03

Hyperparameters Tuning Using Grid Search CV

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Summarizing

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What Have We Learnt

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Area Under the Curve and Confusion Matrix

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Plot the Classification Report

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Let’s See If Cross Validation Layers Help Us

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Visualizing Cross Validation Score

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Features Improvement

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Conclusion

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Course Content

Section 1. Introduction

What is Machine Learning

Data Science Playground

First Image Classifier

Section 2. Data Science and Machine Learning

Recommender System Using

Data Science vs Machine Learning vs Artificial Intelligence

Summarizing It All

Section 3. AI Project Life Cycle

AI Project Framework

Step 1 Problem Definition

Step 2 Data

Step 3 Evaluation

Step 4 Features

Step 5 Modelling

Step 5 Data Validation

Step 6 Course Correction

Tools Needed for AI Project

Section 4. Python the Most Powerful Language

What is Programming Language

Python Interpreter and First Code

Python 3 vs Python 2

Formula to Learn Coding

Data Types and Basic Arithmetic

Basic Arithmetic Part 2

Rule of Programming

Section 5. Python the Most Powerful Language Part 02

Mathematical Operators and Order of Precedence

Variables and Their BIG No No

Statement vs Expression

Augmented Assignment Operator

String Data Type

String Concatenation

Type Conversion

String Formatting

Indexing

Section 6. Python the Most Powerful Language Part 03

Immutability

Built-in Function and Methods

Boolean Data Type

Exercise (Skipped – No Video Link)

Data Structure and Lists

Lists Continued

Matrix from Lists

List Methods

List Methods 2

Section 7. Python the Most Powerful Language Part 04

Creating Lists Programmatically

AND OR Keywords

If Else Statement

Intro to Process of Coding Conditionals

Sets Data Types

Tuple Data Types

Most Used Methods on Dictionaries

Dictionary Key is Unchangeable

Dictionary

Boolean Result of Different Values

Section 8. Python the Most Powerful Language Part 05

Logical Operators

Identity Operator

For Loop and Iterables

Nested For Loop

Exercise For Loop (Skipped – No Video Link)

Range Function

While Loop

Continue Break Pass Keywords

Exercise Draw a Shape (Skipped – No Video Link)

Section 9. Python Part-2

Functions

Scope of a Function

Exercise (Skipped – No Video Link)

Args and Kwargs

Good Programming Practices

Doc String

Return Keyword

Default Parameters

Parameter vs Argument

Why of Functions