NumPy, Pandas and Matplotlib A-Z™ for Machine Learning

Course Curriculum

Chapter 1: NumPy – Setups

Lecture 1: Course Syllabus Walkthrough

Lecture 2: Installing Jupiter Notebook

Lecture 3: Installing of NumPy

Lecture 4: Importing NumPy

Chapter 2: NumPy – Introduction

Lecture 1: What is NumPy

Lecture 2: What is Arrray

Lecture 3: Types of Array

Lecture 4: What is Dimension

Lecture 5: Exploring – Row Before Column – Why?

Lecture 6: Identifying an Array

Lecture 7: Scalar vs Vector vs Matrix vs Tensor

Chapter 3: NumPy – Creating Arrays

Lecture 1: First Time Creating an Array

Lecture 2: Creating an Array from a Tuple

Lecture 3: Creating a Zero Dimensional Array

Lecture 4: Avoiding Errors of "Multiple Arguments"

Lecture 5: Creating a 1-D Array

Lecture 6: Creating a 2-D Array

Lecture 7: Creating a 3-D Array

Chapter 4: NumPy – Data Type

Lecture 1: Understanding NumPy Data Type

Lecture 2: Forcing a Data Type of an Array

Chapter 5: NumPy – Challenges and Solution – Creating Arrays

Lecture 1: The Challenges

Lecture 2: The Challenges – text

Lecture 3: Solution to Challenge 1a

Lecture 4: Solution to Challenge 1b

Lecture 5: Solution to Challenge 1c

Lecture 6: Solution to Challenge 1d

Lecture 7: Solution to Challenge 1e

Lecture 8: Solution to Challenge 2a

Lecture 9: Solution to Challenge 2b

Lecture 10: Solution to Challenge 2c

Lecture 11: Solution to Challenge 2d

Lecture 12: Solution to Challenge 2e

Lecture 13: Solution to Challenge 2f

Chapter 6: NumPy – Creating Arrays – (Others)

Lecture 1: Array of Zeros

Lecture 2: Arrays of Ones

Lecture 3: Empty Arrays

Lecture 4: How to use arange()

Lecture 5: How to use linspace()

Lecture 6: How to use reshape()

Chapter 7: NumPy – Attributes of an Array

Lecture 1: How to find the attributes of an Array – (ndim, shape, size, dtype, itemsize)

Chapter 8: NumPy – Challenges and Solutions – Creating Arrays (More)

Lecture 1: The Challenges

Lecture 2: The Challenges – Text

Lecture 3: Solution to Challenge 1a

Lecture 4: Solution to Challenge 1b

Lecture 5: Solution to Challenge 1c

Lecture 6: Solution to Challenge 2a

Lecture 7: Solution to Challenge 2b

Lecture 8: Solution to Challenge 2c

Lecture 9: Solution to Challenge 2d

Lecture 10: Solution to Challenge 2e

Lecture 11: Solution to Challenge 2f

Lecture 12: Solution to Challenge #3

Lecture 13: Solution to Challenge #4

Chapter 9: NumPy – Array Sorting and Concatenation

Lecture 1: Array Sorting

Lecture 2: Array Concatenation

Chapter 10: NumPy – 1-D Array Indexing and Slicing

Lecture 1: Understanding how indexing and Slicing work on 1-D Arrays

Chapter 11: NumPy – Challenges and Solution – 1-D Array Indexing & Slicing

Lecture 1: The Challenges

Lecture 2: The Challenges – Text

Lecture 3: Solution to Challenge 1a

Lecture 4: Solution to Challenge 1b

Lecture 5: Solution to Challenge 1c

Lecture 6: Solution to Challenge 1d

Lecture 7: Solution to Challenge 1e

Lecture 8: Solution to Challenge 1f

Lecture 9: Solution to Challenge 1g

Lecture 10: Solution to Challenge 1h

Lecture 11: Solution to Challenge 1i

Lecture 12: Solution to Challenge 1j

Lecture 13: Solution to Challenge 1k

Lecture 14: Solution to Challenge 1l

Lecture 15: Solution to Challenge 1m

Chapter 12: NumPy – Creating an Array from Existing Array

Lecture 1: With Less Than, Greater Than or Equal To

Lecture 2: Even and Odd Numbers

Lecture 3: Two Conditions

Chapter 13: NumPy – Challenges and Solutions – Creating an Array from Existing Array

Lecture 1: The Challenges

Lecture 2: The Challenges – Text

Lecture 3: Solution to Challenge #1

Lecture 4: Solution to Challenge #2

Lecture 5: Solution to Challenge #3

Lecture 6: Solution to Challenge #4

Lecture 7: Solution to Challenge #5

Chapter 14: NumPy – 2-D Array Indexing and Slicing

Lecture 1: Selecting Elements of 2-D Array

Lecture 2: Slicing In 2-D Array

Chapter 15: NumPy – Challenges and Solution – 2-D Array Indexing & Slicing

Lecture 1: The Challenges

Lecture 2: The Challenges – Text