Deep Learning & Computer Vision: an Introduction is the perfect course for students who want exposure to Machine Learning. This course will cover topics such as: Artificial Neural Networks, how to install Python, and Handwritten Digit Recognition.
- No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory.
- Working knowledge of Python would be helpful if you want to run the source code that is provided.
- Design and Implement a simple computer vision use-case: digit recognition
- Confidently move on to more complex and comprehensive material on these topics
- Grasp the theory underlying deep learning and computer vision
- Understand use-cases for computer vision as well as deep learning
- Analytics professionals, modelers, big data professionals who haven’t had exposure to machine learning
- Engineers who want to understand or learn machine learning and apply it to problems they are solving
- Product managers who want to have intelligent conversations with data scientists and engineers about machine learning
- Tech executives and investors who are interested in big data, machine learning or natural language processing
- MBA graduates or business professionals who are looking to move to a heavily quantitative role
Chapter 01: Look Long, Look Deep
Lesson 01: Introduction: You, This Course &Us!
Lesson 02: Artificial Neural Networks: Perceptrons Introduced
Lesson 03: Computer Vision: an Introduction
Lesson 04: Perceptron Revisited
Lesson 05: Deep Learning Networks: an Introduction
Lesson 06: Installing Python: Anaconda & PIP
Lesson 07: Code Along: Handwritten Digit Recognition – I
Lesson 08: Code Along : Handwritten Digit Recognition – II
Lesson 09: Code Along: Handwritten Digit Recognition – III
Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi, and Navdeep Singh have honed their tech expertise at Google and Flipkart. Together, they have created dozens of training courses and are excited to be sharing their content with eager students. The team believes it has distilled the instruction of complicated tech concepts into enjoyable, practical, and engaging courses.
Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft
Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too
Swetha: Early Flipkart employee, IIM Ahmedabad and IIT Madras alum
Navdeep: Longtime Flipkart employee too, and IIT Guwahati alum