Practical Machine Learning with Python

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Installation of Anaconda

Lecture 3: Jupyter Notebook Basics

Lecture 4: Data Sets

Chapter 2: Python Programming

Lecture 1: Arithmetic Operators

Lecture 2: Comparison or Relational Operators

Lecture 3: Logical or Boolean Operators

Lecture 4: Bitwise Operators

Lecture 5: Assignment Operators

Lecture 6: Special Operators

Lecture 7: Math using 'math' library

Lecture 8: Variables

Lecture 9: Datatypes

Lecture 10: Typecasting

Lecture 11: Booleans

Lecture 12: Strings

Lecture 13: Special Characters in a String !!!

Lecture 14: How to Split and Strip a String ???

Lecture 15: Introduction to Lists

Lecture 16: Lists Slicing and Reverse Order !!!

Lecture 17: Kinds of Lists

Lecture 18: Concatenate Strings Using join()

Lecture 19: How to add two Lists ???

Lecture 20: Introduction to Dictionary

Lecture 21: Dictionary & It's Methods

Lecture 22: Nested Dictionary

Lecture 23: Create Dictionary Using zip()

Lecture 24: Tuples

Lecture 25: Set

Lecture 26: if…elif….else

Lecture 27: while loop

Lecture 28: range()

Lecture 29: for loop

Lecture 30: Reserve Keywords

Lecture 31: Built in Functions

Lecture 32: User Defined Functions

Lecture 33: Anonymous or Lambda Functions

Lecture 34: File IO Operations

Chapter 3: Numpy

Lecture 1: What is Numpy and Why is it necessary ???

Lecture 2: Creation & Metadata of Numpy Arrays – 1 D & Multi – Dimensional

Lecture 3: What is Broadcasting ???

Lecture 4: Numpy Built in Functions

Lecture 5: Data Types

Lecture 6: How to Convert one data type to another ???

Lecture 7: Matrix Multiplication

Lecture 8: How to change shape of numpy array ???

Lecture 9: How to apply slicing on numpy array ???

Lecture 10: How to apply Boolean indexing on numpy array ???

Lecture 11: How to filter data in numpy ???

Lecture 12: Numpy Statistical Methods !!!

Lecture 13: How to Sort, find Min. & Max of Numpy Array ???

Lecture 14: What is Stacking & Splitting ???

Lecture 15: Copy Vs. View ???

Chapter 4: Pandas

Lecture 1: What is a Series ???

Lecture 2: What is DataFrame ???

Lecture 3: How to View Metadata of Dataframe ???

Lecture 4: How to Rename Columns & Indices in a Dataframe ???

Lecture 5: How to Transpose Dataframe ???

Lecture 6: How to Slice a DataFrame ???

Lecture 7: Apply Boolean Indexing on Dataframe

Lecture 8: How to deal Missing values ???

Lecture 9: How to Replace Values in a Dataframe ???

Lecture 10: How to Search, Extract Words & Create New Columns ???

Lecture 11: How to Set and Unset Index ???

Lecture 12: Apply Builtin & Customized Functions

Lecture 13: What is value_counts() method ???

Lecture 14: The groupby() & associated methods

Lecture 15: Lets Concat & Append !!!

Lecture 16: Merge It !!!

Lecture 17: Reshape it – stack() & unstack()

Lecture 18: Pivoting !!!

Lecture 19: Melt it !!!

Lecture 20: Convert Categorical to Dummy Variables

Lecture 21: What is crosstab() method ???

Lecture 22: String Methods – upper(), extract(), replace(), split() methods

Lecture 23: Regular Expressions !!!

Lecture 24: Application of contains() method

Lecture 25: Application of startswith() method

Lecture 26: Apply Multiple String Methods at a Time

Lecture 27: How to Manipulate Column Names

Lecture 28: Show Columns Based on Keyword

Lecture 29: Application of read_csv() method

Lecture 30: How to read Tabbed File ???

Lecture 31: How to load Fixed Width Files ???

Lecture 32: How to Read JSON data from URL, File Or Variable ???

Lecture 33: Web Scraping HTML Data

Lecture 34: Web Scraping XML Data

Lecture 35: Web Scraping through API Call

Lecture 36: Export DataFrame to CSV File

Lecture 37: How to Load Encoded Data Files ???

Lecture 38: How to deal Bad data while Loading File ?

Lecture 39: Select Columns Based on DataType

Chapter 5: Time Series Analysis

Lecture 1: How to Convert non-timestamp to timestamp data ???

Lecture 2: What if it has Invalid data ???

Lecture 3: What is Unix Time and How to convert it ???