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Machine Learning for Absolute Beginners - Level 2
Getting Started
Welcome! (2:19)
Anaconda Installation (4:22)
JupyterLab Overview (3:51)
Working with a Jupyter Notebook (14:16)
Python Fundamentals for Data Science
Overview (2:52)
Variables and Data Types (7:22)
Strings (7:44)
Lists (9:44)
IF and For-Loop Statements (7:08)
Functions (7:59)
Dictionaries (11:01)
Classes, Objects, Attributes, and Methods (7:28)
Importing Modules (7:34)
Libraries for Data Science Projects (7:03)
Exercise #1 - Python Fundamentals (0:33)
Introduction to the Pandas Library
Overview (2:59)
Series Data Structure (1D) (12:41)
DataFrame Data Structure (2D) (4:52)
Data Selection in a DataFrame (14:55)
Exercise #2 – Pandas Series and DataFrame (0:34)
Loading Data into a DataFrame
Overview (1:14)
Kaggle and the Titanic Dataset (5:48)
Loading a Tabular Data File (6:35)
Adjusting the Loading Parameters (13:06)
Preview the DataFrame (8:14)
Using Summary Statistics (4:48)
The Concept of Methods Chaining (5:17)
Sorting and Ranking (3:13)
Filtering (4:53)
Grouping (4:52)
Exercise #3 – Data Loading and Analysis (0:34)
Data Cleaning and Transformation
Overview (2:07)
Removing Columns or Rows (4:17)
Removing Duplicate Rows (8:37)
Renaming Column Labels (3:32)
Dropping Missing Values (7:29)
Filling-in Missing Values (3:31)
Creating Dummy Variables (8:16)
Exporting Data into Files (2:39)
Exercise #4 – Data Cleaning and Transformation (0:27)
Course Summary
Let's Recap and Thank You! (2:45)
Exercise #3 – Data Loading and Analysis
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