Machine Intelligence – an Introductory Course
Machine Intelligence – an Introductory Course, available at Free, has an average rating of 3.85, with 10 lectures, based on 161 reviews, and has 14607 subscribers.
You will learn about Machine Learning algorithms Artificial Intelligence algorithms Information Retrieval algorithms Deep Learning algorithms Quantum Computing algorithms Computer Vision algorithms Natural Language Processing algorithms This course is ideal for individuals who are Aspiring and Professional Data Scientists and Machine Learning Engineers. or Students pursuing their PhD and looking for a refresher course. It is particularly useful for Aspiring and Professional Data Scientists and Machine Learning Engineers. or Students pursuing their PhD and looking for a refresher course.
Enroll now: Machine Intelligence – an Introductory Course
Summary
Title: Machine Intelligence – an Introductory Course
Price: Free
Average Rating: 3.85
Number of Lectures: 10
Number of Published Lectures: 10
Number of Curriculum Items: 10
Number of Published Curriculum Objects: 10
Original Price: Free
Quality Status: approved
Status: Live
What You Will Learn
- Machine Learning algorithms
- Artificial Intelligence algorithms
- Information Retrieval algorithms
- Deep Learning algorithms
- Quantum Computing algorithms
- Computer Vision algorithms
- Natural Language Processing algorithms
Who Should Attend
- Aspiring and Professional Data Scientists and Machine Learning Engineers.
- Students pursuing their PhD and looking for a refresher course.
Target Audiences
- Aspiring and Professional Data Scientists and Machine Learning Engineers.
- Students pursuing their PhD and looking for a refresher course.
This course focuses on the theoretical aspects of the field of Data Science and Machine Learning. It helps the students to quickly gain an in-depth overview of different algorithmic techniques used in various domains and applications. This course features external links to further enhance the experience and reinforce the concepts acquired. It also provides easy explanations of popular and useful research papers that are driving this field forward.
Course Curriculum
Chapter 1: Survival Analysis
Lecture 1: Introduction to Survival Analysis
Lecture 2: Censorship
Lecture 3: The Survival Function and the Hazard Function
Lecture 4: Kaplan-Meier Estimate and Nelson Aalen Fitter
Lecture 5: Survival Regression – Cox Proportional Hazard Regression Model
Chapter 2: Information Retrieval
Lecture 1: Introduction to Information Retrieval
Lecture 2: Text Preprocessing
Lecture 3: Term-Document Incidence Matrix
Lecture 4: Inverted Index
Lecture 5: Retrieval Vector Space Model
Instructors
-
Taimur Zahid
Machine Learning Engineer
Rating Distribution
- 1 stars: 13 votes
- 2 stars: 18 votes
- 3 stars: 35 votes
- 4 stars: 49 votes
- 5 stars: 46 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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