Python+for+ML.pdf,programming for machine learning

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1. Python For Machine Learning
SAMPRITI CHATTERJEE

2. Agenda
►Why do we need Machine Learning?
►What is Machine Learning?
►Life cycle to build a model with ML
► What is Python?
►Importance of Python
►Important libraries in Python
Agenda

3. What is data?
Why do we need Machine Learning?
What do we need
ML?
►Data becomes unstructured or semi-structured
►Business insights from the data
►Reduce production cost
►Build model based on the data to give the ability to the
machine to predicts on its own

4. Data in the Past days
Small
Structured
Manageable
Data in the past days

5. Data in the Recent days
Huge
Unstructured/ Semi structured
Not manageable with the traditional methods
Data in the recent days

6. Life Cycle Of Data Mining
Life Cycle Of Machine Learning
Understand the business
problem
Data Acquisition Data Cleaning
Exploratory data
Analysis
Machine Learning
Algorithm
Predict your model
accuracy

7. What is Machine Learning?
Machine learning is a sub-set of artificial intelligence (AI) that allows the system to automatically learn and
improve from experience without being explicitly programmed
Model Building Testing Data Training Data
What is Machine Learning?

8. Traditional Programming Vs Machine Learning
Traditional Programming Machine Learning
Da
ta
Prog
ram
Output
Model
Data
Output
Traditional programming Vs Machine Learning

9. Types of Machine Learning
●Supervised Learning
●Unsupervised Learning
●Reinforcement Learning
Types of Machine Learning

10. What is Python?
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Python is a popular high level, object oriented and interpreted language
●High level
●Object oriented
●Interpreted

11. Benefits of Python
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Graphical user interface
Web development using
Python
Length of the program is
short
Mathematical computation can be
done easily
1
2
3
Python is simple and
beginner friendly language
4
5

12. Types of Machine Learning
●Numpy
●Pandas
●Matplotlib
●Seaborn
●Scikit-learn
Important libraries in Python

13. Thank You!
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