Diving Into Machine Learning: Let's Begin!

 

Great! Let's take our first step into the world of Machine Learning. Imagine your dataset as a collection of patient data, including their ages, cholesterol levels, and more. You can find this dataset on Kaggle, a fantastic platform for various datasets:

[Heart Disease Dataset on Kaggle](https://lnkd.in/gh_AVEWx)

To get started, download "heart.csv" from the provided link. Once you have the CSV file, we'll use Jupyter Notebook to import it into Python.

**Here's how:**

1. **Import the necessary library:**
  In Jupyter Notebook, use the Pandas library to handle your data.

  ```python
  import pandas as pd
  ```

2. **Read the CSV file:**
  Replace `"the path where your csv is located"` with the actual path where you saved "heart.csv."

  ```python
  df = pd.read_csv("the path where your csv is located")
  ```

   [Insert an image here for reference.]

By executing these lines, you've successfully imported your dataset. You can explore the first few rows using `df.head()` or the last rows with `df.tail()`.

Stay tuned for my upcoming posts, where we'll delve into more details and start building Machine Learning algorithms. Happy coding! 🚀