Internship ppt done in igeeks technology machine learning with Python where several projects using basic machine learning algorithms has been done

1. Department of Electronics and Communication Engineering.
Presentation by
Mr. Yashwanth T J
USN : 4PM18EC097
8th Semester, Dept. of E&CE,
PESITM, Shivamogga.
Under the Guidance of
Ms . Lavanya R
Assistant Professor
Dept. of E&CE, PESITM, Shivamogga.

2. CONTENTS
 Introduction to the Company Profile
 Details of Training
 Task Performed
 Skills Accomplished
 Conclusion
 References
 Internship Certificate
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3. INTRODUCTION TO
COMPANY PROFILE
• Igeeks Technologies Bangalore
based company explicitly active for
(Android/J2ME) Software
Programming solutions and Mobile
Application Development services as
well as Wireless Application(WAP)
Development.
• Igeeks Internship program offers
students an hands-on opportunity to
work with the company in their
desired field of expertise.
OUR SERVICES
Development | Training |Consulting
Contact:
IGEEKS Technologies,
No: 19, MN Complex, 2nd Cross,
Sampige Main Road, Malleswaram
Bangalore- 560003.
www.igeekstechnologies.com
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4. DETAILS OF TRAINING
1st WEEK
• Python Basics
• Introduction to Machine Learning
2nd WEEK
• Classification of ML
• Features of ML
3rd WEEK
• Detailed Study on Linear Regression
Algorithm Logistic Regression and its
Applications
4th WEEK
• Project Based on ML Algorithms
• Developing project and Testing
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5. TASK PERFORMED
ML is a field of computer science, an application of artificial
intelligence, which provides computer systems the ability to learn with
data and improve from experience without being explicitly
programmed.
Introduction:
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6. TASK PERFORMED
Project Title: “Real Time Eye Detection in Face ”
 Eye detection and recognition in faces from an image or a video is a
popular topic in biometrics research.
 Eye recognition technology has widely attracted attention due to its
enormous application value and market potential, such as real-time video
surveillance system.
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7. TASK PERFORMED
Algorithm Used :
1. HAAR CASCADE
Haar cascade is an algorithm that can detect objects in images, irrespective of
their scale in image and location. This algorithm is not so complex and can run
in real-time.
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8. TASK PERFORMED
Steps Involved in Haar cascade Implementation:
1. Haar Feature Selection
2. Creating Integral Images
3. Adaboost Training
4. Cascading Classifiers
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9. TASK PERFORMED
Methodology:
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10. TASK PERFORMED
Result : Output Image of Stored Image.
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11. SKILLS ACCOMPLISHED
 Technicalskills:
• Python basics
• ML Algorithms
• Basics of python libraries and datasets
 Soft skills:
• Teamwork
• Communication skills
 Managementskills:
• Project management
• Time management and more
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12. CONCLUSION
• This internship has been an excellent and
rewarding experience.
• It was a great opportunity to improve
personal and professional skills.
• These valuable skills have boosted my
professional skills to a higher level and
prepare me for futurecareer.
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13. REFERENCES
 C. Thurau and V. Hlavac, “Pose primitive based human action
recognition in videos or still images,” in Proc. CVPR, 2008, pp. 1–8.
 D. Weinland and E. Boyer, “Action recognition using exemplar-based
embedding,” in Proc. CVPR, 2008, pp. 1–7.
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14. CERTIFICATE
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