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Abhinaba Banerjee
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Data Ingestion, Data Transformation, Model Training, and Model Evaluation, Model Hyperparameter Tuning
In this part of the blog series on End-to-End Machine Learning project implementation, we will go through the steps of Exploratory Data Analysis(EDA) and Model Building by Jupyter Notebook. This is a continuation of Part 1 where we set up the project and created the relevant Python files.
We will also do modular coding for data ingestion, data transformation, and model training to understand how the steps can be implemented in a Python file and how one file can call the other. The main goal of the modular coding we are using here is to reuse the code for future end-to-end projects when needed and customize them accordingly. We must not use this blog to understand EDA in detail or Machine Learning in detail since there are a plethora of high-quality blogs, articles, videos, and courses available, so those topics are not covered in depth. This blog or series of blogs primarily aims to understand better how the whole pipeline and End-to-End project works.
Exploratory Data Analysis (EDA)
The project structure is given for convenience.
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I write about Data and Cloud https://www.linkedin.com/in/obhinaba17/ https://github.com/abhigyan631
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