Mastering Practical Usage of Machine Learning: Save Models & Automate Data Prep!

In this video, we dive deep into the practical side of machine learning, guiding you through the essential steps of saving models and automating data preparation. Whether you're a beginner or looking to enhance your ML skills, this tutorial has something for everyone.

🔍 Key Takeaways:

Learn how to save your trained machine learning models for future use.
Discover the power of automation in data preprocessing for streamlined workflows.
Master practical tips for efficient model sharing and collaboration.

📁 Timestamps:

00:00 - Recap
00:25 - Introduction & Objective of the video
02:40 - Clean and Save the Models
08:17 - Automation of Data Pre-Processing work
11:53 - Automation of SMOTE Balancing
16:14 - Create or Save the Automated Module
18:35 - Using the Saved Module to clean or pre-process the data
23:40 - Using the Saved Trained Models for prediction
30:08 - Combining prediction with the input data and exporting that to excel

👩‍💻 Resources - Data, Code and Tools Used:
Data used to test the model - https://github.com/LEARNEREA/Data_Sci...
Output of the prediction - https://github.com/LEARNEREA/Data_Sci...

Data Balancing & Model Building - https://github.com/LEARNEREA/Data_Sci...
Saved Ensemble Model - https://github.com/LEARNEREA/Data_Sci...
Saved SMOTE Logistic Model - https://github.com/LEARNEREA/Data_Sci...
Data Pre-Prep. Automated Module - https://github.com/LEARNEREA/Data_Sci...
Code Created in the video - https://github.com/LEARNEREA/Data_Sci...

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