Visual aids to get started with machine learning. This guide presents steps from collecting data to deploying your model with basic machine learning algorithms and key points to remember.

1. Machine
Learning
in
Pictures
a Pocket Guide to Practical
10Just steps

2. Identify
the problem
Come up
with a rough
strategy

3. Collate and
prepare data
Split into
training and
testing sets

4. Cleaning and normalizing are
part of data preparation.
Also do some exploratory
data analysis to familiarize
yourself with the data
before diving into ML.

5. PRO
TIP
Use correlation analysis to
select best predictors for
your ML model.
NOT APPLICABLE FOR UNLABELLED DATA

6. SUPERVISED LEARNING
when data is labelled/pre-categorized
UNSUPERVISED LEARNING
when data is not labelled beforehand
FYI

7. Select a suitable ML
algorithm for modeling
on training data

8. DON'T TOUCH THE TEST
DATA UNTIL MODEL IS
TRAINED

9. N U M B E R S
D A T E S
S A L E S
Q U A N T I T Y
B A S I C A L L Y
A N Y T H I N G
M E A S U R A B L E
S T R U C T U R E D
D A T A
for

10. L I N
E A
R
R
E G
R
E S S I O
N

11. P O E S S I O N
L R
Y G
N E
O R
M I A L

12. L O G I S T I C
R E G R E S S I O N

13. SUPPO
RTVECTORM
ECHANISM

14. Decision
TRE ES

15. Random
Forest

16. U N S U P E R V I S E D
C L U S T E R I N G
anomaly
detection

17. Unstructured
Data I M A G E S / S O U N D / T E X T
F O R

18. N
N
N
N
I
|
I
N E U R A L N E T W O R K S

19. score
model
against
test data
use
resampling
methodsif
lessdata

20. B O O T S T R A P
RESAMPLING

21. FOLDS
1
2
n
Train Test
C R O S S V A L I D A T I O N
RESAMPLING

22. EVALUATE MODEL
using test data set
with following metrics
R E G R E S S I O N
M S P E
M S A E
R S Q U A R E
A D J U S T E D
R S Q U A R E
P R E C I S I O N
R E C A L L
A C C U R A C Y
L O G -
L O S S
C L A S S I F I C A T I O N

23. Adjust model
hyperparameters
and retrain the
model
Use the best model to..

24. ..make
predictions
on fresh
data

25. web and mobile
applications.
DEPLOY MODEL FOR
10

26. Delight
your
users
and keep improving.

27. made with love
by Rajat Gupta
using CANVA
Rajat Gupta
Data Science Practice Lead
Sci-Bi Software Systems