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Machine Learning by Sanjay Upadhyay

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Agile Testing Alliance hosted it's 16th Meetup in Pune on 9th Dec, 2017. Sanjay Upadhyay from Amdocs gave a session on Machine Learning as a part of this meetup. All the rights belongs to the author.

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Machine Learning by Sanjay Upadhyay

  1. 1. Machine Learning Sanjay Upadhyay -SW Test Manager Amdocs 09/12/2017
  2. 2. Machine Learning Sanjay Upadhyay -SW Test Manager Amdocs 09/12/2017 Presented as a part of ATA Pune 16th Meetup on 9th Dec, 2017
  3. 3. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs3 What is learning ??? ”Learning denotes changes in a system that ... enable a system to do the same task more efficiently the next time.” – Herbert Simon “Learning is constructing or modifying representations of what is being experienced.” – Ryszard Michalski “ Learning is making useful changes in our minds.” – Marvin Minsky
  4. 4. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs4 • I don’t know, may be learning from machines? • Making machines learn something a.k.a. programming machine software • Learning with help of computers • Learning through online courses (!!!) What is Machine Learning ?
  5. 5. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs5
  6. 6. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs6 The Learning
  7. 7. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs7 • How did our brain process the images? • How did the grouping happen? • Human brain processed the given images - learning • After learning the brain simply looked at the new image and compared with the groups classified the image to the closest group - Classification • If a machine has to perform the same operation we use Machine Learning • We write programs for learning and then classification, this is nothing but machine learning Machine Learning
  8. 8. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs8 How exactly do we teach machines? Data as Input Text Files, Spread sheet SQL Data bases Abstracting the data Representation of the data in structural format through the algorithm chosen Generalization The practical application happens here where the learning from the previous step is used to develop an insight
  9. 9. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs9 What are the steps used in Machine Learning? There are 5 basic steps used to perform a machine learning task: Collecting data Preparing the data Training a model Evaluating the model Improving the performance
  10. 10. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs10
  11. 11. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs11 The main advantage of ML • Learning and writing an algorithm • Its easy for human brain but it is tough for a machine. It takes some time and good amount of training data for machine to accurately classify objects • Implementation and automation • This is easy for a machine. Once learnt a machine can process one million images without any fatigue where as human brain can’t • That’s why ML with bigdata is a deadly combination
  12. 12. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs12 Applications of Machine Learning Banking / Telecom / Retail Identify: • Prospective customers • Dissatisfied customers • Good customers • Bad payers Obtain: • More effective advertising • Less credit risk • Fewer fraud • Decreased churn rate
  13. 13. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs13 Main parts in Machine Learning process Any Machine Learning algorithm has three parts 1. The Output 2. The Objective Function or Performance Matrix 3. The Input Example: Email Spam Classification 1. The Output: Categorize email messages as spam or legitimate. 2. Objective Function: Percentage of email messages correctly classified. 3. The Input: Database of emails, some with human-given
  14. 14. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs14 ML in Software Development & Testing • SOFTWARE DESIGN • REQUIREMENT TRACING • CODE GENERATION • SOFTWARE ESTIMATION • SOFTWARE TESTING • GUI TESTING • CI Automation
  15. 15. Information Security Level 2 – Sensitive © 2017 – Proprietary & Confidential Information of Amdocs15 Journal Citation • WWW.Slideshare.net • https://www.analyticsvidhya.com/blog/2015/06/machine-learning-basics/# • https://www.toptal.com/machine-learning/machine-learning-theory-an-introductory-primer • https://www.google.co.in Machine Learning Courses & Tutorials Coursera - Machine Learning - Stanford University | Coursera + YouTube Series Lecture Collection | Machine Learning - YouTube Machine Learning | Coursera Practical Machine Learning - Johns Hopkins University | Coursera Neural Networks for Machine Learning - University of Toronto | Coursera Udacity - Intro to Machine Learning Course | Udacity DataCamp - Python Machine Learning: Scikit-Learn Tutorial, Introduction to Machine Learning - Online Course EdX - Learning From Data (Introductory Machine Learning) OCW MIT - Machine Learning, Introduction to Neural Networks Hackr.io: Best Machine Learning Tutorials Recommended by the Programming Community
  16. 16. Thank you

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