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Data Wizardry: Unleashing the Potential of Data Engineering and Machine Learning
Mammoth Interactive Courses Introduction
Preface
01 How To Learn Online Effectively (13:46)
00 About Mammoth Interactive (1:12)
Source Files
Python Introduction
What Is Python (4:48)
Intro To Python (4:37)
Course Overview
Course Overview (3:26)
Source Files - Course Overview
Source Files
Complete Source Files - Data Engineering
(Prerequisite) Introduction to Machine Learning
What Is Machine Learning (5:26)
Types Of Machine Learning Models (12:17)
What Is Supervised Learning (11:04)
What Is Unsupervised Learning (8:17)
How Does A Machine Learning Agent Learn (7:38)
What Is Inductive Learning (4:11)
Performance Of A Machine Learning Algorithm (4:14)
Handle Noise In Data (5:22)
Powerful Tools With Machine Learning Libraries- (12:11)
(Prerequisite) Introduction to Python
Introduction (4:42)
Variables (19:17)
Type Conversion Examples (10:04)
Operators (7:04)
Operators Examples (21:52)
Collections (8:23)
Lists (11:38)
Multidimensional List Examples (8:05)
Tuples Examples (8:34)
Dictionaries Examples (14:24)
Ranges Examples (8:30)
Conditionals (6:41)
If Statement Examples (10:16)
If Statement Variants Examples (11:18)
Loops (7:00)
While Loops Examples (11:30)
For Loops Examples (11:18)
Functions (7:47)
Functions Examples (9:16)
Parameters And Return Values Examples (13:46)
Classes And Objects (11:13)
Classes Example (13:11)
Objects Examples (9:54)
Inheritance Examples (17:26)
Static Members Example (11:03)
Summary And Outro (4:06)
Load, clean and encode data
Load And Clean A Public Dataset (8:55)
What Is One-Hot Encoding (10:02)
Build X And Y Data With One Hot Encoding (4:57)
Logistic Regression With One Hot Encoding (2:20)
Data engineering for machine learning
Scale And Encode Data With Scikit-Learn (3:47)
What Is Scaling Data (6:36)
Build, Train And Test A Machine Learning Model (4:37)
Build regression and discretizer models
Compare Decision Tree And Linear Regression Models (6:26)
What Is The Kbins Discretizer (4:54)
Bin Data With Kbins Discretizer (3:42)
Compare Binned Regression Models (3:39)
Build A Linear Regression Model On Stacked Data (3:20)
What Is K Means Clustering (11:58)
Data transformation and feature selection for ridge regression
Build Univariate Nonlinear Transformatio (1:55)
What Is Gaussian Probability Distribution- (2:31)
What Is Poisson Distribution (1:08)
Build X Y Data With Poisson Distribution In Numpy (3:34)
What Is Logarithmic Data Transformation (2:34)
Build A Ridge Regression Model (3:41)
Logistic Regression With One Hot Encoding
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