Want to be a Data Scientist ➟ Build Projects,

Here are 5 Steps to Build a Successful Data Science Project!

1 - Define the Problem You want to Solve :

Begin by clearly defining the problem you want to solve and the desired outcome.

This will aid in the direction of your data exploration and Model building process.

2 - Data Preprocessing & Visualisation :

Gather and clean the data.

It's a time-consuming step, but it is necessary to ensure that your model is trained on accurate data.

Explore and visualize the data to identify patterns and trends, use tools such as Matplotlib and Seaborn.

3 - Model Building :

It's now time to build and test your model. To build, train, and test your model,

Iterate your model by experimenting with different algorithms and hyperparameters until you achieve the desired result.

4 - Evaluate the model:

Once you have a trained model, evaluate its performance using metrics such as accuracy, precision, and recall.

Cross-validation can be used to ensure that your model is not overfitting or underfitting the data.

5 - Communication :

Inform stakeholders about your findings and results.

Create clear and compelling visualizations of your results using data visualization tools.

Prepare to answer questions and explain your methodology to non-technical audiences as well.

Bonus - If you want to learn how to preprocess and visualize data, come to our live data analysis class on February 18th.

Sign up before the slot closes 👇👇👇:

www.lighthall.co/class/039c72c6-8051-45f8-92b8-907782bbe5bf

That's a wrap! & Thank you for Reading

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