How to Structure Data Science Projects

How to Structure Data Science Projects

In this article, we will be stopping at Model Building. Check out PART-2 for deployment using Heroku and streamlit. I will be going through every one of the above-mentioned steps about the Resale Car Price Prediction projected mentioned earlier.

When should I start my first project?

The question that every data science/machine learning aspirant comes across at least once, while they are relatively new to this field is that

Is it too early to start my own project? What more do I need to learn before I start working on my own project?

The answer to this question varies from person to person but a general rule of thumb is that once you feel comfortable with your command over a few fundamental subtopics of machine learning, you’re good to go! It’s never too early. We learn faster and retain more DOING a task, than watching someone perform the same or reading a book about it.

Which Project Should I Choose?

Pick any one topic that you want to work on (regression, classification, computer vision, NLP, etc.), try to come up with real-life applications for the topic, and make a map, a rough sketch, of all the steps you need to take, to get the idea out of your brain and into the real world.

Early in your data science career, you do not need to worry if your project has any real-world significance or possible business outcomes. The fundamental focus of this is to test yourself on your skills and find the areas where you lack knowledge.

From here on, I will be walking you through my first data science project, Resale Price Prediction of Cars. Take a look at the deployed version of this project to get an idea of how your project should look upon completion.

The code snippets used in this post are extracted from the code on my GitHub. RESALECARS

Getting Started:

Here are the steps that you will need to adhere to while doing any data science project :

  1. Data Collection
  2. Data Preprocessing
  3. Exploratory Data Analysis
  4. Feature Engineering
  5. Model Building
  6. Deployment

In this article, we will be stopping at Model Building. Check out PART-2 for deployment using Heroku and streamlit. I will be going through every one of the above-mentioned steps about the Resale Car Price Prediction projected mentioned earlier.

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