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1. A
PRESENTATION ON
"Agriculture Production Optimization Engine"
For
INDUSTRIAL TRAINING (7CS7-30)
Submitted to :
Sandeep Tuli
Department of CSE
Submitted By :
Jaya Kumari & EkamdeepKaur
B.Tech., VII Semester
Fourth Year

2. Training Details
• Technology Learned: Data Science and Machine Learning with Python
• Company: Global Institute of Technology, Jaipur
• Training Duration: 4th July 2022 – 17 August 2022
• Mode of Training: Online
PRESENTATION TITLE 2

3. Introduction to Data Science
❑ Data Science is a study of analyzing and predicting
the data. It is a way to analyze the pattern from the
data and bring out meaningful insightful for
business critical decisions and expansions.
❑ Data Science is a blend of Mathematics, Statistics
and Programming to analyze the data.
❑ Data Science is all about the present and future.
That is finding out the trends based on historical
data which can be useful for marking present
decisions and finding patterns which can be
modelled and can be used for predictions to see
what things may look like in the future.

4. Need to learn Data Science
With the amount of data that is being generated and the evolution in
the field or Analytics, Data Science has turned out to be a necessity for
companies.
• Social Media sites
• Business transactions
• Location-based data
• Sensors
• Digital photos, videos
• Consumer behavior (Online store transaction)

5. Skills that are required to be a Data Scientist:
• Mathematics and
Statistics
• Programming(Python)
• Domain Knowledge

6. Python Libraries used:
NumPy is a library for
the Python programming
language, adding support
for large, multi -
dimensional arrays
and matrices, along with
a large collectionof high-
level mathematical functi
ons to operate on these
arrays.
Pandas is a software library
written for the Python
programming language for data
manipulationand analysis.In
particular, it offers data structure
and operationsfor manipulating
numerical tables and time series.
Matplotlib is
a plottinglibrary for
the Python programming
language and its numerical
mathematics extension NumPy.

7. Application used :
Open – source web application that
allows you to create and share
documentsthat contain live code,
equations, visualizations and narrative
text.

8. Some Application
of Data Science
• Security
• Banking and Finance
• Internet Search
• Image Processing
• Speech Recognition
• Gaming
• Health Care
• Self-Driving Cars

9. Data Visualization
Datavisualization is the representation of data through use of common graphics, such as charts, plots,
infographics, and even animations. These visual displays of information communicate complex data
relationships and data-driven insights in a way that is easy to understand. Some plots are shown:

10. Introduction to Machine Learning
➢ Machine Learning is the field of study that gives
computers the capability to learn without being
explicitly programmed. ML is one of the most exciting
technologies that one would have ever come across.
As it is evident from the name, it gives the computer
that makes it more similar to humans: The ability to
learn. Machine learning is actively being used today,
perhaps in many more places than one would expect.
➢ Machine Learning is an AI technique that teaches
computers to learn from experience. Machine
learning algorithms use computational methods to
“learn” information directly from data without relying
on a predetermined equation as a model.

11. Types of Machine Learning

12. Project
Agriculture Production Optimization
Engine
This Project is intended on Precision
Farming.
➢ We have to optimize Productivity
➢ By Understanding requirements of
climatic and Soil Conditions for Crops
➢ Helping us to Cope up with weather
unpredictability

15. THANK YOU