Kaggle is not just a competitive data science platform, it's one of the largest repositories for datasets, it is also a Cloud IDE where you can build and deploy a model.
Check details in this 🧵
RT Appreciated
#Kaggle #BlackTechTwitter
Check details in this 🧵
RT Appreciated
#Kaggle #BlackTechTwitter
Click on the "<> Code" menu option as illustrated in the image below.
This will take you to the Kaggle IDE Environment
This will take you to the Kaggle IDE Environment
You are right on the Kaggle IDE. Ah-mazing right? 😊
You can see trending notebooks already. what a platform!!
Don't get distracted.
Click on "New Notebook"
You can see trending notebooks already. what a platform!!
Don't get distracted.
Click on "New Notebook"
This will take you to an environment similar to Jupyter Notebook. This is the Integration Development Environment window.
The default language here is Python.
First, click on the "Power Button" to start your environment.
might take a few seconds.
The default language here is Python.
First, click on the "Power Button" to start your environment.
might take a few seconds.
It is time to add data to your notebook.
Click on Add data at the top right as illustrated in the image below
Click on Add data at the top right as illustrated in the image below
Wow... There are several data to work with here and you can even upload your own dataset.
For this example, we are using the Wine Quality Dataset.
Go ahead and click on "Add"
For this example, we are using the Wine Quality Dataset.
Go ahead and click on "Add"
Click on the "Play icon" at the top left to rerun the notebook.
This will print your working directory and from the result, we see that the name of the dataset is WineQT.csv, and also the directory.
Click on "+Code" to add a new line of code
This will print your working directory and from the result, we see that the name of the dataset is WineQT.csv, and also the directory.
Click on "+Code" to add a new line of code
Type what you can see in this image.
data is the variable to store our dataset. pd.read_csv is the pandas function for reading CSV data.
copy the exact file path from the top right as shown in the image below.
Press "Shift Key + Enter Key" to run the code
data is the variable to store our dataset. pd.read_csv is the pandas function for reading CSV data.
copy the exact file path from the top right as shown in the image below.
Press "Shift Key + Enter Key" to run the code
now that you have loaded the data into a variable called "data", it is time to check the top 5 items on the table.
Do this by typing "data.head()"
This will display the top 5 rows in your data.
Do this by typing "data.head()"
This will display the top 5 rows in your data.
To activate TPU or GPU, check the video on this THREAD
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