ML Process Course
This is the public repository for the ML Process Course. In this course, we take you through the end-to-end process of building a Machine Learning Model. We did not build this course ourselves. We stood on the shoulders of giants. We think its only fair to credit all the resources we used to build this course, as we could not have created this course without the help of the ML community.
Use the discount link for our 3 course bundle (limited time 68% off!) --> The Machine Learning A-Z Bundle
Flashcards
Please go to Ankiweb.net to download Anki and to sign up for account. Please go here to download the flashcards for this course.
Table of Contents
- Coding Workbooks for Each Course
- Data Science Blogs
- Applying ML
- Problem Framing
- Data Collection
- Data Preprocessing
- Exploratory Data Analysis
- Feature Engineering
- Cross Validation
- Feature Selection
- Imbalanced Data
- Modeling
- Model Evaluation
Coding Workbooks for Each Course
Data Science Blogs
2. Applying ML
3. Problem Framing
4. Data Collection
5. Data Preprocessing
6. Exploratory Data Analysis
7. Feature Engineering
Categorical Feature Engineering
Continuous Feature Engineering
8. Cross Validation
9. Feature Selection
10. Imbalanced Data
11. Modeling
Hyperparameter Tuning
Ensembling
12. Model Evaluation
12. Model Productionization