Machine learning
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Machine learning is a feature that allows systems to automatically learn and improve from experience without being explicitly programmed. There are two main types of machine learning problems: supervised learning, where the system is provided example inputs and outputs, and unsupervised learning, where there is no labeled data provided. Machine learning is used in applications such as spam filtering, natural language processing, recommendations, face and object recognition, and autopilot systems.
Machine learning
- 1. Machine Learning ALEN VARGHESE SAJNA BANU SHILPA P
- 2. What is Machine Learning?
- 3. What is the Difference Between a Human and a Computer? Learn From Experience Follow Instructions
- 4. Can Computer Learn from Experience?
- 5. What is Machine Learning? ● Machine learning is feature that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. ● Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
- 6. Definition of Machine Learning ● A computer program is said to learn from experience E with respect to some task T and some performance measure P if its performance on T, as measured by P, improves with experience E.
- 7. Types of problems and tasks
- 8. Types of problems and tasks • Supervised learning • Unsupervised learning
- 9. Supervised learning ●In supervised learning, we are given a data set and already know what our correct output should look like, having the idea that there is a relationship between the input and the output. ● Eg: Spam Detection, Face Detection, Recommendations
- 10. Unsupervised learning ●Unsupervised algorithms do not need to be trained with desired outcome data. Instead, they use an iterative approach called deep learning to review data and arrive at conclusions. ●Eg: Grouping that are somehow similar or related by different variables.
- 11. Spam Filtering
- 12. Email Spam Filtering ●Machine Learning engine uses several keyword to refine emails for us. ●They check for certain keywords and other sentences. ● They also checks type of content, Unclear subject field, If the message is forward, If the subject field contains ambiguous letters etc.
- 13. E-Mail
- 15. Natural Language Processing ●Each time when we use voice search or other voice assistants, our voice is sent to their servers to improve the quality of NLP using Machine Learning Engines.
- 16. Recommendations
- 17. Spotify
- 18. YouTube
- 19. Google Play
- 21. Photos
- 22. Photos
- 23. Photos
- 24. Photos
- 25. Google Maps
- 26. Autopilot in Cars and Airplanes
- 27. Autopilot
- 28. Autopilot
- 29. Interested in Machine Learning? ■Coursera (https://www.coursera.org/learn/machine-learning) ■Udacity (https://www.udacity.com/courses/machine-learning)
Editor's Notes
- #4: What is the Difference Between a Human and a Computer? Human - Learn From Experience Computer - Follow Instructions
- #5: Can Computer Learn from Experience? Yes, That’s exactly what is Machine Learning. For Computers Experience is called as Data.
- #6: the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning is closely related to computational statistics. which also focuses on prediction making through the use of computers
- #7: A computer program is said to learn from experience E with respect to some task T and some performance measure P if its performance on T, as measured by P, improves with experience E.
- #10: we are given a data set and already know what our correct output should look like. Spam Detection, Face Detection, Recommendations there is a relationship between the input and the output..
- #11: do not need to be trained. they use an iterative approach called deep learning to review data and arrive at conclusions.
- #13: Uses keyword to refine
- #16: Each time when we use voice search or other voice assistants, our voice is sent to their servers to improve the quality of NLP.
- #17: Machine Learning helps to bring recommendations based on different attributes. Let’s see few of them.
- #18: See it shows “Your daily mixes”, play the music that you love. Personalized Music According to my taste.
- #19: Here Videos recommended are shown. There is a high I’ll watch these videos.
- #20: Recommended Apps They show apps that are more likely to be downloaded by me. These recommended feature is very much helpful for Advertising.
- #21: Machine learning uses many algorithms to save different information about an image. Using these information, they can predict what the image contains.
- #22: Recognizing people in my Album
- #23: When I search for “DOGS”, It shows photos of dogs in my Album.
- #26: It shows live traffic updates. It can predict the time that you arrive at any destination.
- #28: This is tesla’s autopilot. It uses Machine learning to improve itself. It’s already proven computer can drive better than a human.
- #29: Lets watch a video, how tesla’s autopilot is can save life
- #30: There are so many Libraries available in Python