We launched Tranfer Learning in July 2020 with the simple idea of helping the community track newly published research papers and suggest the best courses to understand them.

One of the questions I get most often is: “What are your favorite data science or machine learning resources?” This website is dedicated to answering that.

So you can find a collection of some of the best machine learning, artificial intelligence, and data science resources and of course resources.

We can cover up more than 3 domains : Language, Machine Learning and Medecine.

What is transfer learning ?

Transfer learning is a machine learning method where a model developed for a task is reused as the starting point for a model on a second task.

It is a popular approach in deep learning where pre-trained models are used as the starting point on natural language or computer vision processing tasks given the vast compute and time resources required to develop neural network models on these problems.

Transfer-Learning Use cases

There are three main types of transfer learning.

  • Inductive Transfer Learning
  • Transductive Transfer Learning
  • Unsupervised Transfer Learning

What is transfer learning for humans ?

Transfer learning is the best way to learn because it is the distillation of abstract knowledge from one learning domain or task and the reuse of that knowledge in a related domain or task.

Now, there are a lots of learning platforms (Coursera, Udemy, Udacity) where if you have some basics, your can discover new knowledges in another domains and innovate with new solutions in your domain.