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How to use
Machine Learning
effectively
So many
questions may
come to mind…
These must be
answered.
So you consult
many people.
With machine
learning, it can be
made easy.
Why is this so?
It uses historical
data to make
predictions.
It can be broken
down into five
basic steps.
One
Choose data.
What kind of
data are you
going to input?
Stocks
Sales
Scores
These data
depend upon
your need.
Second
Massage or
clean data
Here, you detect
and correct
corrupt data.
You identify
incomplete,
incorrect, …
inaccurate or
irrelevant parts of
the data.
Then, replacing,
modifying, or
deleting them.
Steps 1 and 2
area bout data
collection.
This makes sure
that…
you make the
right data set.
Once you have
your structured
data, …
you can move
on to the next
step.
Third
Split into training
or data set
This is an important
part of evaluating
data.
In training set,
…
you apply the
model you
design.
You assess the
strength of a
predictive
relationship.
In test set, you
test the trained
model.
You are now
ready for the
next step.
Fourth
Apply
algorithm
You apply this
algorithm on the
trained…
that you have
extracted in
step 3.
This is the most
important part.
As you need to
understand this:
What kind of
algorithm you
need to apply…
so you can
achieve the kind
of data you need.
Once you have
your trained
model,…
you need to find
the answer to this:
Is it good
enough?
So let’s talk
about the last
step.
Lastly
Score &
Evaluate
What will you
score and
evaluate?
Score your
trained model.
Evaluate its
performance.
Thank you for
watching!
HOW TO USE MACHINE LEARNING EFFECTIVELY
HOW TO USE MACHINE LEARNING EFFECTIVELY
HOW TO USE MACHINE LEARNING EFFECTIVELY
HOW TO USE MACHINE LEARNING EFFECTIVELY
HOW TO USE MACHINE LEARNING EFFECTIVELY
HOW TO USE MACHINE LEARNING EFFECTIVELY
HOW TO USE MACHINE LEARNING EFFECTIVELY
HOW TO USE MACHINE LEARNING EFFECTIVELY
HOW TO USE MACHINE LEARNING EFFECTIVELY
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HOW TO USE MACHINE LEARNING EFFECTIVELY

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We live in the world where we would like everything to be available in an instant. This is why we have instant noodles, instant coffee, and more things available in a flick of a second.
In business and other activities, we also want things to be readily available the time we need them. This is why artificial intelligence has been developing to cope with the demand of times. Through machine learning we are able to predict future performances of a certain business, an athlete, stocks, sites and many more.
Machine learning is an amazing method of data analysis that automates model building or algorithm. Here is the good thing about this: your past data can be updated once new information is fed. In short, they are able to adapt independently.

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HOW TO USE MACHINE LEARNING EFFECTIVELY

  1. 1. How to use Machine Learning effectively
  2. 2. So many questions may come to mind…
  3. 3. These must be answered.
  4. 4. So you consult many people.
  5. 5. With machine learning, it can be made easy.
  6. 6. Why is this so?
  7. 7. It uses historical data to make predictions.
  8. 8. It can be broken down into five basic steps.
  9. 9. One
  10. 10. Choose data.
  11. 11. What kind of data are you going to input?
  12. 12. Stocks
  13. 13. Sales
  14. 14. Scores
  15. 15. These data depend upon your need.
  16. 16. Second
  17. 17. Massage or clean data
  18. 18. Here, you detect and correct corrupt data.
  19. 19. You identify incomplete, incorrect, …
  20. 20. inaccurate or irrelevant parts of the data.
  21. 21. Then, replacing, modifying, or deleting them.
  22. 22. Steps 1 and 2 area bout data collection.
  23. 23. This makes sure that…
  24. 24. you make the right data set.
  25. 25. Once you have your structured data, …
  26. 26. you can move on to the next step.
  27. 27. Third
  28. 28. Split into training or data set
  29. 29. This is an important part of evaluating data.
  30. 30. In training set, …
  31. 31. you apply the model you design.
  32. 32. You assess the strength of a predictive relationship.
  33. 33. In test set, you test the trained model.
  34. 34. You are now ready for the next step.
  35. 35. Fourth
  36. 36. Apply algorithm
  37. 37. You apply this algorithm on the trained…
  38. 38. that you have extracted in step 3.
  39. 39. This is the most important part.
  40. 40. As you need to understand this:
  41. 41. What kind of algorithm you need to apply…
  42. 42. so you can achieve the kind of data you need.
  43. 43. Once you have your trained model,…
  44. 44. you need to find the answer to this:
  45. 45. Is it good enough?
  46. 46. So let’s talk about the last step.
  47. 47. Lastly
  48. 48. Score & Evaluate
  49. 49. What will you score and evaluate?
  50. 50. Score your trained model.
  51. 51. Evaluate its performance.
  52. 52. Thank you for watching!

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