Machine Learning Tutorial for Beginners – Linear Regression Example in Python [Part 1]

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From a csv file all the way to making predictions and deploying your results. Full end-to-end Tutorial on Machine Learning. 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.
Then, we explain what Linear regression is and how it works. After that, we run the model and make predictions. 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:

Raw Data and Code:

Video 1 – Down and Install Python – Numpy Tutorial:
Video 2 – Pandas Tutorial:
Video 3 – JOINs and UNIONs Tutorial:
Video 4 – Data Visualizations with MatPlotLib:
Video 5 - Data Visualizations with Seaborn:

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 regression model in python?
- How to optimise a machine learning model in python?

Yiannis Pitsillides on Social Media:
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Which ML algorithm do you use the most in your job? Linear Regression is probably in the top 3!

DataYP
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Always providing the most real life examples in order to learn machine learning, God bless you

cubanlincoln
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I watch all your video on python for data science for beginner from 1-5, and this one. Frankly speaking, you did far better than those training provided in edx, coursera, udemy... far better. You know very well what to cover when teaching people to use software for data analysis/analytics. You know where to begin, and what example to give. Thank you very much.

KPAVideoful
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The best course I have ever seen . Really fantastic

rahil
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Good job. Looking forward for the next videos.

daniel
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Great video!
You just summarized my 1 year of postgraduate business analysis degree in 1 hour using Python...🤣

Griffindor
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I think your code can be a bit neater by using native Pandas functions instead of loops etc.whenever possible.
Some tips: You can just put an “r” before the opening quotes to avoid adding backslashes.
Also .fillna is a neater way of dealing with NA values in pandas.
Thanks for the nice tutorial.

Lnd
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Hey Yanis, love your work mate. So valuable, my best source of learning data science, thanks for everything. Question: Whe are you going to release the part2? Looking forward for the next video

leandrop.
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You are a rockstar! what other platform do you have that I can follow and support you. Thank you.

colombarillo
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can you show full projects end to end ? thank you, to aggregate to portfolio

martingarcia
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Aren't you supposed to do a train-test split before preprocessing steps??

shreyasvijayakumar
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Thanks for this wonderful class. please do you mind send me your github link so that i can get access to the datasets. thanks

nkechiesomonu
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why are you deleting videos from your youtube channel??

datawithtess
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