What is machine learning?
Machine learning is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior. Artificial intelligence systems are used to perform complex tasks in a way that is similar to how humans solve problems. Machine learning is one way to use AI.
What is meant by machine learning in Python?
Machine Learning is making the computer learn from studying data and statistics. Machine Learning is a step into the direction of artificial intelligence (AI). Machine Learning is a program that analyses data and learns to predict
the outcome.
COURSE DURATION:
Python Machine Learning is 45 Days course. The training programs are in e-learning video sessions that can be access at anywhere.
ELIGIBILITY:
Graduates/Working professionals
REQUIREMENTS
- PC/Smart Phone with Internet.
- Some programming experience
5 CAREER OPTIONS FOR MACHINE LEARNING
- Software Engineer.
- Software Developer.
- Designer in Human-Centered Machine Learning.
- Data Scientist.
- Computational Linguist.
Course Preview
Course Curriculum
| COURSE CURRICULUM | |||
| 1. What does the course cover? | 00:06:00 | ||
| 2. Introduction | 00:18:00 | ||
| 3. Getting Started with Anaconda | 00:06:00 | ||
| 4. First program | 00:11:00 | ||
| 5. Basics of python | 00:11:00 | ||
| 6. Python Datatypes | 00:11:00 | ||
| 7. Python Operators | 00:11:00 | ||
| 8. Python Lists | 00:10:00 | ||
| 9. Python List Methods | 00:08:00 | ||
| 10. Python Tuples | 00:07:00 | ||
| 11. Python Sets | 00:08:00 | ||
| 12. Python Dictionaries | 00:11:00 | ||
| 13. Python Conditions and If statements | 00:08:00 | ||
| 14. Elif statement | 00:07:00 | ||
| 15. Python Nested if Statement | 00:06:00 | ||
| 16. Nested if example program | 00:06:00 | ||
| 17. Python For Loops | 00:13:00 | ||
| 18. Python While Loop | 00:06:00 | ||
| 19. Python Functions | 00:20:00 | ||
| 20. File Handling | 00:09:00 | ||
| 21. NumPy | 00:12:00 | ||
| 22. Numpy datatypes | 00:07:00 | ||
| 23. Numpy array joining | 00:07:00 | ||
| 24. Numpy array indexing | 00:07:00 | ||
| 25. Python Pandas | 00:20:00 | ||
| 26. Basic machine learning | 00:11:00 | ||
| 27. Data Distribution using Machine learning | 00:10:00 | ||
| 28. Machine Learning – Train/Test | 00:08:00 | ||
| 29. Iris project 1: working with error messages | 00:11:00 | ||
| 30. Iris project 2: Reading Csv Data in to memory | 00:06:00 | ||
| 31. Iris project 3: Visualization | 00:08:00 | ||
| 32. Exploratory data analysis | 00:20:00 | ||
| 33. Linear Regression | 00:16:00 | ||
| 34. Polynomial Regression | 00:15:00 | ||
| 35. Multiple Regression | 00:11:00 | ||
| 36. Decision tree | 00:14:00 | ||
| 37. Support vector Machine | 00:19:00 | ||
| 38. Project: Fake news detection using machine learning | 00:16:00 | ||
| 39. Project: Object detection | 00:13:00 | ||
| 40. Project: image classification | 00:10:00 | ||
| Final Exam | |||
| python new quiz | 00:30:00 | ||
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