Part 2 - Advance Linear Regression | Kaggle Competition | Missing Values | Encoding | Outliers |

This is the second part of the advance linear regression. I have implemented many techniques that help in answering the following question.
How to use function and for loop to play around with data?
How to treat missing values?
How to encode variables?
How to treat outliers?
How to select important columns/features?
How to combine two different models?
Note: It is a lecture series, so make sure to subscribe to the youtube channel and press the bell icon for future updates.

Blogpost: https://www.datasciencenovice.com/2020/10/how-to-prepare-data-machine-learning.html

Notebook: https://github.com/100ravp/Kaggle-House-Price-Prediction

Check out my other playlist:

1) Deep Learning with TensorFlow
https://www.youtube.com/watch?v=jmj1ksiDGYM&list=PLtCJhQPz4XPVmfcl60l5XrWfCAp12mFr3

2) Hands-On with OpenCV
https://www.youtube.com/watch?v=nc_V7DWHWdg&list=PLtCJhQPz4XPWvUF4jU9dv3rQ38dNzNEuu

3) Image classification with Keras
https://www.youtube.com/watch?v=KBPxEiazBz4&list=PLtCJhQPz4XPUiAnWYPbSVMZC5o_CUO3TS

4) Fake News Detection
https://www.youtube.com/watch?v=u22Q27glu2I&list=PLtCJhQPz4XPUPUyy4xe2XfL6Hx-Y3Neqb

5) Data Science Project
https://www.youtube.com/watch?v=ZqI1GSLjW1M&list=PLtCJhQPz4XPU1WvrW7ln2GZVwCsHxVcsw

Follow me on:
My blog: https://www.datasciencenovice.com
GitHub: https://github.com/100ravp
Kaggle: https://www.kaggle.com/sauravprasad
Telegram: https://t.me/datasciencenovice

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#Datacleaning
#Machinelearning

Видео Part 2 - Advance Linear Regression | Kaggle Competition | Missing Values | Encoding | Outliers | канала DS Novice