5 Beginner Friendly Steps to Learn Machine Learning

This video breaks down practical steps on how to learning machine learning with Python. It’s the video I wish I had watched when I started learning machine learning.

My machine learning course – https://dbourke.link/mlcourse
Blog post version of this video – https://dbourke.link/5stepstoml
Learn all of this in one place on DataCamp – http://bit.ly/datacampmrdbourke
Bonus: A 6 step field guide for the modelling phase of machine learning projects – https://dbourke.link/6stepmlfieldguide

Other Links Mentioned (in order)

Step 1 – Learn Python, data science tools and machine learning concepts
Elements of AI – https://www.elementsofai.com/
Python for Everybody on Coursera – https://bit.ly/pythoneverybodycoursera
Learn Python by freeCodeCamp – https://www.youtube.com/watch?v=rfscVS0vtbw
Corey Schafer’s Anaconda Tutorial – https://www.youtube.com/watch?v=YJC6ldI3hWk
Bonus: My Anaconda Blog Post – https://dbourke.link/anaconda
Corey Schafer’s Jupyter Notebook Tutorial – https://www.youtube.com/watch?v=HW29067qVWk

Step 2 – Learn data manipulation, analysis and visualization with pandas, NumPy and Matplotlib
Applied Data Science with Python – http://bit.ly/courseraDS
Codebasics Pandas series – https://www.youtube.com/playlist?list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy
freeCodeCamp NumPy video – https://youtu.be/QUT1VHiLmmI
Sentdex Matplotlib series – https://www.youtube.com/playlist?list=PLQVvvaa0QuDfefDfXb9Yf0la1fPDKluPF

Step 3 – Learn machine learning with scikit-learn
Data School scikit-learn series – https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A
Bonus: fastai machine learning course – https://course18.fast.ai/ml

Step 4 – Learn deep learning and neural networks
Andrew Ng’s deep learning specialization on Coursera – https://bit.ly/courseradl
fastai deep learning curriculum – https://fast.ai

Step 5 – Extra curriculum & books
My favourite machine learning books (video) – https://www.youtube.com/watch?v=7R08MPXxiFQ
Python for Data Analysis by Wes McKinney – https://amzn.to/2Z1QZNp
Hands-on Machine Learning with scikit-learn and TensorFlow by Aurelien Geron – https://amzn.to/2Q8iy4v
The Mechanics of Machine Learning by Terrence Parr and Jeremy Howard – https://mlbook.explained.ai/
A Gentle Introduction to Exploratory Data Analysis (project example) – https://towardsdatascience.com/a-gentle-introduction-to-exploratory-data-analysis-f11d843b8184
How to work on your own machine learning projects (article) – https://towardsdatascience.com/how-to-start-your-own-machine-learning-projects-4872a41e4e9c

Timestamps
0:26 – Who this video is for
0:41 – My style of learning (code first)
1:51 – Step 1, learn Python, data science tools and machine learning concepts
3:10 – Step 2, learn data manipulation, analysis and visualization with Pandas, NumPy and Matplotlib
4:57 – Step 3, learn machine learning with scikit-learn
6:07 – Step 4, learn deep learning and neural networks
7:33 – Step 5, Extra curriculum & books
10:07 – Where can I learn all these skills?
10:47 – How long should all of this take?
11:45 – What about statistics? Probability? Math?
12:19 – What about certifications?

Note: Affiliate links have been used where possible. This means when you click a link and purchase something I may get a percentage of the purchase price. It will not change the price of the item.

Get email updates on my work – https://dbourke.link/newsletter
Support on Patreon – https://bit.ly/mrdbourkepatreon

Connect elsewhere:
Web – https://dbourke.link/web
Quora – https://dbourke.link/quora
Medium – https://dbourke.link/medium
Twitter – https://dbourke.link/twitter
LinkedIn – https://dbourke.link/mpMxSc

source