Machine Intelligence - an Introductory Course

Learn the cutting-edge Algorithms in the field of Machine Learning, Deep Learning, Artificial Intelligence, and more!
Rating: 3.5 out of 5 (81 ratings)
7,528 students
Machine Intelligence - an Introductory Course
Rating: 3.5 out of 5 (81 ratings)
7,528 students
Machine Learning algorithms
Artificial Intelligence algorithms
Information Retrieval algorithms
Deep Learning algorithms
Quantum Computing algorithms
Computer Vision algorithms
Natural Language Processing algorithms

Requirements

  • Understanding of Calculus and Linear Algebra will help better understand most of the concepts discussed here. But you can look for helpful resources alongside studying this course.
Description

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.

Who this course is for:
  • Aspiring and Professional Data Scientists and Machine Learning Engineers.
  • Students pursuing their PhD and looking for a refresher course.
Course content
2 sections • 10 lectures • 40m total length
  • Introduction to Survival Analysis
    02:38
  • Censorship
    03:49
  • The Survival Function and the Hazard Function
    02:36
  • Kaplan-Meier Estimate and Nelson Aalen Fitter
    03:09
  • Survival Regression - Cox Proportional Hazard Regression Model
    06:39
  • Introduction to Information Retrieval
    02:27
  • Text Preprocessing
    04:31
  • Term-Document Incidence Matrix
    01:55
  • Inverted Index
    05:30
  • Retrieval Vector Space Model
    06:54

Instructor
Machine Learning Engineer
Taimur Z.
  • 3.8 Instructor Rating
  • 546 Reviews
  • 22,181 Students
  • 4 Courses

About Me: I am a Machine Learning Engineer, with over two years of experience in the field of Data Science and Machine Learning. I am a Former Teaching Assistant for the Deep Learning Master's Degree Course and the Natural Language Processing Course. I have a Bachelor's Degree in Computer Science, Nanodegrees in Deep Learning and Artificial Intelligence, and a keen interest in all things Data Science.

My Courses: I follow the agile development methodologies to design, create, and publish my courses. I follow small manageable sprints to update my courses regularly by either adding new content to existing courses or creating an entirely new course. This allows me to not only respond to and structure my courses based on direct student feedback, but also, to add the latest skill in demand as quickly as possible.