Supervised Machine Learning Example in Python – KAGGLE COMPETITION – Code is Provided

Solve your first Kaggle Competition! From a csv file all the way to making predictions and deploying your results. Full end-to-end Tutorial on Machine Learning in Python. We start by explaining the Machine Learning Process. Then, we move on to the Data pre-processing phase where we clean and transform our data. We show some methods on how to identify the most important variables.
After that, we run the model and make predictions. Every time we run a model, we submit it into Kaggle to get our score on the evaluation dataset. Then, we go over a few methods on how to improve our results & predictions. We provide the raw data and the code! Hope you enjoy!

Data Analytics Course Link:
http://ipidata.teachable.com/

Raw Data and Code:
https://github.com/Pitsillides91/Python-Tutorial-2022-/tree/main/Classification%20Example

Video 1 – Down and Install Python – Numpy Tutorial:
https://youtu.be/nZyKxP04co4
Video 2 – Pandas Tutorial:
https://youtu.be/JjFifnK3bVg
Video 3 – JOINs and UNIONs Tutorial:
https://youtu.be/tMv74JmjZ_Y
Video 4 – Data Visualizations with MatPlotLib:
https://youtu.be/SQfEeFNAvdE
Video 5 - Data Visualizations with Seaborn:
https://youtu.be/CsqCLaLMGn4
Video 6 – Machine Learning Example – Regression:
https://youtu.be/Q0Q4x58h_BA


Table of content:
- What is machine Learning?
- How to run machine learning in python?
- Supervised machine learning example in python
- What is the machine learning process
- How to clean data in python?
- How to do data pre-processing python machine learning
- How to deal with outliers in python?
- How to investigate the distributions in python?
- How to do feature engineering in python?
- How to find the most important variables in python?
- What is a machine Learning regression model and how it works?
- How to run machine learning classification model in python?
- How to optimise a machine learning model in python?
- How to Run XGBoost in Python?


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