Calories Burnt Prediction Project using Machine Learning
Naveen
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In this article, we will learn how to develop a machine learning model using Python which can predict the number of calories a person has burnt during a workout based on some biological measures.
You can download Calories dataset from here and Exercise dataset from here.
we will import all the necessary libraries and also warnings which we take care of any future warning.

We will now read our dataset using pandas read_csv function and check the top 5 rows with the help of head() function.


We will combine our dataframe with the help of concat function, as we have two different dataframes.

We will now check the shape of our dataset and will check some information about our data.

We will check if our dataset contains null values

We will get some statistical information about the data.

To check the distribution of our column we will be using seaborn’s countplot.




We will check if our columns have positive correlation or negative correlation.



We will now train our model and evaluate on test data.



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Author
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Naveen Pandey has more than 2 years of experience in data science and machine learning. He is an experienced Machine Learning Engineer with a strong background in data analysis, natural language processing, and machine learning. Holding a Bachelor of Science in Information Technology from Sikkim Manipal University, he excels in leveraging cutting-edge technologies such as Large Language Models (LLMs), TensorFlow, PyTorch, and Hugging Face to develop innovative solutions.
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