An Introduction to Python and Machine Learning for Technical SEO

2. “Despite having decades of experience he still took the time
to follow and encourage people just starting out and even
earlier, kicking their impostor syndrome out of the way to
help them get started. Any question answered with a smile
and encouragement, Hamlet was one of a kind”
“He had the perfect hug for any occasion.
And joy. Joy for helping another SEO solve a problem. Joy
for seeing a friend again. Joy for seeing others succeed.”
“Hamlet was a force of nature. An incredibly kind man,
always learning, creating, publishing, leading the way &
elevating others in the journey.”
“An inspiration to me & many, he made ppl realise
they were capable of so much more than what they
thought they could.”
“I never met Hamlet but I greatly respected and looked up
to him for the knowledge, kindness and support he
brought to the SEO community. He inspired so many and
will be very missed. Thoughts are with his family and
friends.”

10. ● General purpose programming language
● Interpreted line by line
● Object orientated
● Designed to be readable
● Open source
● Interactive

11. Code written in the terminal

12. Results printed

16. 20 week online course
Mixture of theory and practical
A range of projects to undertake
Code console & terminal to play and test

17. Wide range of skill
tracks
Interactive exercises
Instant explanations
Challenges and
projects

18. Free mobile app
Learn Python on
the go
Over 200 practice
questions
Code Playground
https://www.sololearn.com/Course/Python/

23. Data extraction & analysis
Scientific Computing
Natural Language
Processing
Machine Learning

25. Data extraction and
analysis to solve
complex problems
Future-proofing your job
Efficiency and time-saving
Automating repetitive
tasks

26. Spend 5 hours a week using
excel

27. Spend 5 hours a week using
excel
Thats 20 hours a month

28. Spend 5 hours a week using
excel
Thats 20 hours a month
Over 200 hours a year

29. Imagine what we
could achieve if we
spent this time on
other important tasks
(that can’t be
automated)

32. Make data driven decisions
Allowing us to focus on other
important optimisation efforts
Confidence in recommendations
Provide concrete insights
Better understand data

35. https://paperswithcode.com/paper/bottom-up-and-top-down-attention-for-image
https://learnpythia.readthedocs.io/en/latest/

42. optimize-images filename.jpg
optimize-images ./

48. https://colab.research.google.com/drive/1zQ8VFcNmwVLKEMwJ3lhTginPoSC5TdpB

49. https://colab.research.google.com/drive/1zQ8VFcNmwVLKEMwJ3lhTginPoSC5TdpB

51. Log File analysis
Validate hreflang
Identify duplicate URLs
Perform competitor
analysis
Automate page speed
audits

53. Identify which sections of the site are linked to the most. Does
this impact performance? Are there sections we can improve
with internal linking?

59. https://www.expertsystem.com/machine-learning-definition/

60. https://www.expertsystem.com/machine-learning-definition/
Run a script
to train the
computer,
using a
dataset

61. https://www.expertsystem.com/machine-learning-definition/
Run a script
to train the
computer,
using a
dataset
Summarise
& Visualise
the dataset

62. https://www.expertsystem.com/machine-learning-definition/
Run a script
to train the
computer,
using a
dataset
Summarise
& Visualise
the dataset
Evaluate
the
algorithms

63. https://www.expertsystem.com/machine-learning-definition/
Run a script
to train the
computer,
using a
dataset
Summarise
& Visualise
the dataset
Evaluate
the
algorithms
Make
Predictions

64. RankBrain NLP
Computer
Vision
BERT

66. https://ipullrank.com/machine-learning-guide/how-to-set-up-a-chatbot/

101. https://github.com/BritneyMuller/colab-notebooks

114. https://www.fullstackpython.com/
https://www.tensorflow.org/learn