Uploaded December 2019 | Updated September 2026, 3 weeks ago
This is the first video (part2) of my applied machine learning series.
In this video, I talk about the motivation for this channel and then show how you can create a re-usable machine learning framework for simple tabular datasets.
Due to the size of the video, I split them into 2 sub-episodes:
Episode 1.1 consists of motivation, setting up a web based IDE, creating an empty framework and creating model training
Episode 1.2 shows how the trained model can be used for inference.
The whole idea behind this episode is to create code which is re-usable, looks good and can be applied to many different kinds of problem without changing a lot of code.
Please let me know in comments what you want to learn and I will make it happen :)
Github for this episode: github.com/abhishekkrthakur/mlframework
LinkedIn: linkedin.com/in/abhi1thakur
Twitter: twitter.com/abhi1thakur
Kaggle: kaggle.com/abhishek
This is the first video (part2) of my applied machine learning series.
In this video, I talk about the motivation for this channel and then show how you can create a re-usable machine learning framework for simple tabular datasets.
Due to the size of the video, I split them into 2 sub-episodes:
Episode 1.1 consists of motivation, setting up a web based IDE, creating an empty framework and creating model training
Episode 1.2 shows how the trained model can be used for inference.
The whole idea behind this episode is to create code which is re-usable, looks good and can be applied to many different kinds of problem without changing a lot of code.
Please let me know in comments what you want to learn and I will make it happen :)
Github for this episode: github.com/abhishekkrthakur/mlframework
LinkedIn: linkedin.com/in/abhi1thakur
Twitter: twitter.com/abhi1thakur
Kaggle: kaggle.com/abhishek
