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Machine Learning with Python: The Complete Course
Introduction
Overview of Contents (1:59)
The Bigger Picture (6:02)
The Problem Landscape (10:53)
Defining Data Science (6:20)
Demystifying AI ML Data Science (3:46)
Exploring the Data Scientists Toolbox (10:18)
Introduction to Data Scientist's Toolbox
Overview of Contents (1:56)
Python 2.7 vs Python 3.5 (4:32)
Installation Setup (8:00)
Datatypes Overview (5:17)
Spyder tour (3:14)
Datatypes demo (22:55)
Datatyppes Numpy (10:18)
Datatypes Pandas (9:22)
Data Engineering (21:33)
Data Engineering (5:13)
Data Engineering (9:24)
Functions (6:59)
Data Visualization (31:37)
Exploratory Data Analysis, Feature Engineering and Hypothesis Testing
Overview of Contents (1:24)
Machine Learning Methodology (7:10)
Exploratory Data Analysis (3:13)
Univariate Analysis (7:48)
Univariate Analysis (16:36)
Bivariate Analysis (27:50)
Feature Engineering (18:22)
Introduction to Statistics (17:11)
Probability Distributions (7:42)
Machine Learning
Overview of Contents (2:50)
Introduction to Machine Learning (22:43)
Supervised Learning (4:09)
Simple Multiple Linear Regression (12:18)
Regression Demo (17:43)
Classification Logistic Regression (11:32)
Classification Logistic Regression Demo (12:07)
Decision Trees (22:09)
Decision Trees Demo (23:00)
Unsuervised Learning Clustering (11:13)
Unsupervised Learning CLustering Demo (9:18)
Unsupervised Learning Association Rules (5:51)
Model Evaluation Regression (6:06)
Model Evaluation Regression Demo (10:35)
Model Evaluation Classification (8:11)
Model Evaluation Classification Demo (14:22)
Regularization Hyperparameter tuning (11:37)
Bias Variance Tradeoff (6:30)
Cross Validation (7:57)
Hyperparameter Tuning (5:22)
Cross Validation Hyperparameter Demo (19:03)
Ensemble Modeling (14:17)
Random Forest Bagging (7:57)
XGBoost Boosting (4:07)
RF XGB Demo (15:00)
Capstone Project
Overview of Contents (4:42)
Project Use Case Overview (9:56)
Defining the Problem Statement (6:54)
Business SolutionBluepring (15:13)
Explore Define a ML use case (9:00)
EDA and Feature Engineering (16:16)
Approach for Model Devlopment Evaluation Optimization (15:09)
Storyboarding (8:17)
The Problem Landscape
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