( Python Data Science Training : https://www.edureka.co/python ) This Edureka video on "Python For Data Science" explains the fundamental concepts of data science using python. It will also help you to analyze, manipulate and implement machine learning using various python libraries such as NumPy, Pandas and Scikit-learn. This video helps you to learn the below topics: 1. Need of Data Science 2. What is Data Science? 3. How Python is used for Data Science? 4. Data Manipulation in Python 5. Implement Machine Learning using Python 6. Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check out our Python Training Playlist: https://goo.gl/Na1p9G

1. Copyright © 2018, edureka and/or its affiliates. All rights reserved.

2. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Agenda
Need of Data Science01
What Is Data Science?02
How Python Is Used For Data Science?03
Data Manipulation In Python04
Implement Machine Learning Using Python05
Demo06

3. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Need Of Data Science

4. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Need Of Data Science
THEN
NOW
THEN
❖ To handle and analyze extremely
large datasets/ data flow
❖ Faster & better Decision making
❖ No Predictions
❖ Reduce Production Cost
❖ Gain business Insights
❖ Build intelligence & ability in
machines

5. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
What Is Data Science?

6. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
What Is Data Science?
Data Science, known as data driven science makes
use of scientific methods, processes, algorithms and
systems to extract knowledge or insights with the goal
to discover hidden patterns from the raw data.

7. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Data Life Cycle
Data Scientist provides a ONE STOP SOLUTION for all these operations

8. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Programming Languages For Data Science
Python

9. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Programming Languages For Data Science
Python

10. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Python For Data Science

11. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Python For Data Science
01
Python
It is simple and easy to learn

12. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Python For Data Science
02
01
Python
Fit for many platforms
It is simple and easy to learn

13. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Python For Data Science
02
03
01
It is high level and interpreted language
Python
03
Fit for many platforms
It is simple and easy to learn

14. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Python For Data Science
02
03
04
01
It is high level and interpreted language
Fit for many platforms
It is simple and easy to learn
Python
03
04
Perform data manipulation,
analysis and visualization

15. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Python For Data Science
02
04
05
01
Powerful libraries for Machine learning
applications & other scientific computations
Perform data manipulation,
analysis and visualization
It is high level and interpreted language
Fit for many platforms
It is simple and easy to learn
Python
0303
04

16. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Data Manipulation

17. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Data Manipulation
Using data manipulation, you can extract, filter and transform your data
quickly and efficiently.
NumPy
Pandas
LIBRARIES USED:

18. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
NumPy & Pandas
NumPy is a Python
package which stands for
‘Numerical Python
conda install numpy
import numpy
NumPy
Pandas is built on top of
NumPy. It is used for data
manipulation and analysis.
Pandas
conda install pandas
import pandas

19. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Demo: Basic Operations

20. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Overview of Machine Learning

21. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Machine Learning
Machine learning is a type of Artificial Intelligence that allows software applications to learn from the
data and become more accurate in predicting outcomes without human intervention.

22. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Types Of Machine Learning
1
2
3
Supervised Learning
Unsupervised Learning
Reinforcement Learning

23. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Types Of Machine Learning
1
2
3
Supervised Learning
Unsupervised Learning
Reinforcement Learning

24. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Supervised Learning
Supervised Learning is where you have input variable (X) and output variable (Y) and
you use an algorithm to learn the mapping function from the input to the output.
Y = f(X)
Linear Regression Logistic Regression Decision Tree
Random forest Naïve Bayes Classifier
ALGORITHMS:

25. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Demo: Logistic Regression

26. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Unknown value of variable or the
variable to be predicted
Logistic Regression
❑ Logistic regression produces results in a binary format
❑ Used to predict outcome of a categorical dependent variable
❑ Outputs – Yes/ no, true/ false, high/ low, pass/ fail
Y = a + bX
Dependent
Variable
It is a point at which the line cuts
the y- axis
Y
intercept
known variable or the variable
related to dependent variable
Independent
Variable
It is the tangent angle made by
the line
Slope
Relation Between Dependent & Independent variable:

27. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Demo: Logistic Regression
A car company has released a new SUV in the market. Using the previous data about the sales of
their SUV’s, they want to predict the category of people who might be interested in buying this.
PROBLEM
STATEMENT

28. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Types Of Machine Learning
1
2
3
Supervised Learning
Unsupervised Learning
Reinforcement Learning

29. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Unsupervised Learning
Unsupervised Learning is the training of a model using information that is neither
classified or labelled. Unsupervised learning is also called as clustering analysis.
Hierarchical ClusteringK- Means Clustering
ALGORITHMS:

30. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Types Of Machine Learning
1
2
3
Supervised Learning
Unsupervised Learning
Reinforcement Learning

31. Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Reinforcement Learning
It is an area of machine learning where a RL agent learns from the consequences of its
actions, rather than from being taught explicitly. It selects its actions on basis of its past
experiences (exploitation) and also by new choices (exploration).
Q- learning
ALGORITHMS:
SARSA DQN

32. Session In A Minute
Need Of Data Science Python For Data ScienceWhat is Data Science?
Data Manipulation DemoImplement ML
Unsupervised Learning
Reinforcement Learning
Supervised Learning

33. Copyright © 2017, edureka and/or its affiliates. All rights reserved.