Deep Learning in Practice II: Transfer Learning Projects
What you'll learn
- Develop complex deep learning projects using Transfer Learning
- Efficiently organize and structure deep learning projects
- Develop reusable libraries to reduce development time of deep learning projects
- Understand how to perform efficient training of classification projects with Transfer Learning
- Compare between deep learning models
- Learn State of the Art Classification Models
- Conduct training on local machine and Google Colab
Requirements
- Understand the basic concepts of machine learning (recommended, but not required)
- Be familiar with Python programming language and data structures (Numpy, Pandas)
- Understand the basic concepts of neural networks (recommended)
Description
You want to start developing deep learning solutions, but you do not want to lose time in mathematics and theory?
You want to conduct deep learning projects, but do not like the hassle of tedious programming tasks?
Do you want an automated process for developing deep learning solutions?
This course is then designed for you! Welcome to Deep Learning in Practice, with NO PAIN!
This course is the second course on a series of Deep Learning in Practice Courses of Anis Koubaa, namely
Deep Learning in Practice I: Basics and Dataset Design: the student will learn the basics of conducting a classification project using deep neural networks, then he learns about how to design a dataset for industrial-level professional deep learning projects.
Deep Learning in Practice II: Transfer Learning and Models Evaluation: the student will learn how to manage complex deep learning projects and develop models using transfer learning using several state-of-the-art CNN algorithms. He will learn how to develop reusable projects and how to compare the results of different deep learning models in an automated manner.
Deep Learning in Practice III: Deployment of Deep Learning Models: the student will learn how to deploy deep learning models in a production environment. We will present the deployment techniques used in industry such as Flask, Docker, Tensorflow Serving, Tensorflow JavaScript, and Tensorflow Lite, for deployment in a different environment. Despite important, this topic has little coverage in tutorials and documentations.
Deep Learning in Practice II: Transfer Learning Projects
This course introduces you to transfer learning and demonstrate to you how to use transfer learning in real-world projects.
In this course, I demonstrate how to conduct training of a deep learning classification model using transfer learning.
Besides, you will learn how to evaluate the performance of a model with some pre-configured libraries that makes it easy to obtain the results and interpret them.
I also provide ready-to-use Google Colab Notebooks with all codes used in this course.
The same code can be easily adapted and reused for any classification project in an automated way.
Who this course is for:
- Someone who learned the concepts of deep learning, but want to master the practical aspects of deep learning projects
- PhD and Master students doing thesis on deep learning
- Any enthusiast about artificial intelligence and deep learning
- Computer vision practitioners
- Anyone who would like to learn about best practices in deep learning
- Anyone who like to quickly start with deep learning without having a background in it
Course content
- Preview06:11
- 02:13About the instructor
- Preview01:06
- 00:14Get the course Material and Notbooks
Instructor
![Anis Koubaa](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.4 Instructor Rating
- 3,531 Reviews
- 12,433 Students
- 6 Courses
I am Anis Koubaa, a Full Professor in Computer Science at Prince Sultan University and the Director of the Robotics and Internet-of-Things research lab. I am also R&D Director at Gaitech Robotics in China and Senior Researcher in CISTER/INESC TEC and ISEP-IPP, Porto, Portugal. I have been the Chair of the ACM Chapter in Saudi Arabia since 2014. I am also a Senior Fellow of the Higher Education Academy (HEA) in UK.
I received several distinctions and awards including the Rector Research Award in 2010 at Al-Imam Mohamed bin Saud University, and the Rector Teaching Award in 2016 at Prince Sultan University.
I have been teaching Programming courses for more than 16 years in particular Java and Web technologies, and different computer science courses. Programming is my passion for me and I have developed many software and applications. I have been also teaching robotics and developing several program with ROS in both academia and industry.
I am the Editor of three books on Robot Operating System (ROS) with Springer publisher, which are in the top 25% of most downloaded book in Springer database.
I have a lot of tutorials and course on the Internet provided on my YouTube Channel. I am very excited to provide my courses on Udemy to students around the world with practical hands-on activities.
My teaching philosophy is based on Teaching by Demonstration, where I like to explain the concepts by demonstrating them with real-world illustrations. The students will be mainly Learning by Doing.