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Here is what you will Learn from Simplifying Machine Learning with PyCaret in Python

1. Introduction to Machine Learning

1. Getting Started
2. Machine Learning and its Types

2. Regression

1. Regression with PyCaret
2. Exploratory Data Analysis
3. Getting Familiar with the PyCaret Environment
4. Building the Model
5. Coding Challenge: Train Random Forest Model

3. Classification

1. Classification with PyCaret
2. Exploratory Data Analysis
3. Getting Familiar with the PyCaret Environment
4. Building the Model
5. Coding Challenge: Make Predictions and Plot Model

4. Clustering

1. Clustering with PyCaret
2. Exploratory Data Analysis
3. Getting Familiar with the PyCaret Environment
4. Building the Model

5. Anomaly Detection

1. Anomaly Detection with PyCaret
2. Exploratory Data Analysis
3. Getting Familiar with the PyCaret Environment
4. Building the Model

6. Natural Language Processing

1. Natural Language Processing with PyCaret
2. Exploratory Data Analysis
3. Initializing the NLP Environment
4. Creating and Assigning the Topic Model
5. Initializing the Classification Environment

7. Deploying a Machine Learning Model

1. Streamlit
2. Insurance Charges Prediction Web App
3. Iris Classification Web App
4. Deploying an Application to Streamlit Cloud
5. Coding Challenge: Visualize Dataframe as Line Chart

8. Conclusion

1. Closing Thoughts