Section 01: Introduction | |||
Introduction to Course | 00:06:00 | ||
What is Machine Learning | 00:05:00 | ||
Life Cycle | 00:05:00 | ||
Section 02: Numpy Library | |||
Introduction to Numpy Library | 00:07:00 | ||
Creating Arrays from Scratch | 00:06:00 | ||
Creating Arrays from Scratch Continued | 00:05:00 | ||
Array Indexing and Slicing | 00:10:00 | ||
Numpy Array Functions and Shape Modification | 00:09:00 | ||
Mathematical Operations on Numpy Arrays | 00:07:00 | ||
Introduction to Pandas Library | 00:10:00 | ||
Working with Pandas DataFrames | 00:07:00 | ||
Slicing and Indexing with Pandas | 00:07:00 | ||
Create DataFrame and Explore Dataset | 00:08:00 | ||
Data Analysis with Pandas DataFrame | 00:12:00 | ||
Other Useful Methods in Pandas Library | 00:04:00 | ||
Section 03: Matplotlib | |||
Introduction to Matplotlib | 00:06:00 | ||
Customizing Line Plots | 00:08:00 | ||
Create Plot Using DataFrame | 00:09:00 | ||
Standard Scaler to Scale the Data | 00:06:00 | ||
Encoding Categorical Data | 00:11:00 | ||
Sklearn Pipeline and Column Transformer | 00:12:00 | ||
Evaluation Metrics in Sklearn | 00:07:00 | ||
Linear Regression | 00:12:00 | ||
Evaluation of Linear Regression Model | 00:10:00 | ||
Section 04: Polynomial Regression | |||
Polynomial Regression | 00:13:00 | ||
Polynomial Regression Continued | 00:13:00 | ||
Sklearn Pipeline Polynomial Regression | 00:11:00 | ||
Decision Tree Classifier | 00:13:00 | ||
Decision Tree Evaluation | 00:07:00 | ||
Random Forest | 00:06:00 | ||
Support Vector Machines | 00:09:00 | ||
K-means Clustering | 00:04:00 | ||
KMeans Clustering – Hands On | 00:12:00 | ||
Data Loading and Analysis | 00:06:00 | ||
Dimensionality Reduction with PCA | 00:09:00 | ||
Hyper Parameter Tuning | 00:09:00 | ||
Summary | 00:02:00 | ||
Resource | |||
Resource – Machine Learning with Python Course | 00:00:00 | ||
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