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Copyright © 2018, edureka and/or its affiliates. All rights reserved.
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
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Need Of Data Science
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
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
What Is Data Science?
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.
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Data Life Cycle
Data Scientist provides a ONE STOP SOLUTION for all these operations
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Programming Languages For Data Science
Python
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Programming Languages For Data Science
Python
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Python For Data Science
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Python For Data Science
01
Python
It is simple and easy to learn
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
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
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
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
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Data Manipulation
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:
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
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Demo: Basic Operations
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Overview of Machine Learning
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.
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Types Of Machine Learning
1
2
3
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Types Of Machine Learning
1
2
3
Supervised Learning
Unsupervised Learning
Reinforcement Learning
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:
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Demo: Logistic Regression
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:
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
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Types Of Machine Learning
1
2
3
Supervised Learning
Unsupervised Learning
Reinforcement Learning
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:
Copyright © 2018, edureka and/or its affiliates. All rights reserved.
Types Of Machine Learning
1
2
3
Supervised Learning
Unsupervised Learning
Reinforcement Learning
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
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
Copyright © 2017, edureka and/or its affiliates. All rights reserved.
Python for Data Science | Python Data Science Tutorial | Data Science Certification | Edureka

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Python for Data Science | Python Data Science Tutorial | Data Science Certification | Edureka

  • 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.