It is a seminar project made by me . It is about the the data science and it's uses. As computer science student this is a important to manage the data and how to deal with easily and efficiently.

1. TITLE:PRESENTATION ON hyper transport
Presented by:-
Name-Goutam Nayak
Section-ECE
Semester:-3rd
Regd no-2201298516
Guided by-

2. What Is Hyper Transport:
Hyper Transport is a scalable packet-based, high-
bandwidth, and low-latency point-to-point interconnect
technology intended to interconnect processors and also
link them to I/O peripheral devices. Hyper Transport was
initially devised as an efficient replacement for traditional
system buses for on-board communications.

3. History Of Hyper Transport:
• In earlier time there is no much more data of user in the internet so
all data are stores in excel form .But gradually number user increases
so to store the data
of user large no of ware house are made. This data is used to deal
with
real world problem like to improve the business strategy improve
user experience.

4. Data collection :
The first step of data science is data collection .This involves
gathering data from various sources and cleaning it to ensure
accuracy .It’s important to use reliable sources and appropriate
methods for collecting data.
Data is collected from different source like
1.web data, e-commerce
2.Financial transactions, bank/credit transactions
3.Online trading and purchasing
4.Social network

5. Data analysis:
Data analysis involves exploring and
interpreting data to identify patterns
and trends. This can be done using
statistical methods and visualization
tools .It’s important to have a
hypothesis and a plan analysis.
 According to a report Google process
20PB data daily.
 Facebook has 60TB of daily logs.
 eBay has 6.5PB of user data.

6. Machine learning:
Machine learning is a subset of
data science that involves
using algorithm to learn
patterns from data. It can be
used for predication and
classification tasks. It’s
important to choose the right
algorithm and evaluates its
performance.

7. Feature of data science:

8. Conclusion:
Data science is a powerful tools for extracting insights from data.
To be effective, it requires a combination of technical skills and
domain expertise . By following the techniques and strategies
discussed one can become a more effective data scientist.