Hands-on Meta-Learning

Are you struggling with small data to train your deep learning models? Applied machine learning is on the rise in many domains and Industries. The unavailability of a large amount of data becomes a bottleneck to many problem statements in ML/AI. The time to train complex deep learning algorithms and models also needs high computational power. In this course, we will learn about Meta-Learning, a subfield of machine learning to train the model with fewer training data and make the model learn faster. Meta-learning is gaining popularity in various industries for deploying deep learning models. This workshop is beneficial for all data scientists, machine learning(ML) researchers and professionals to learn the latest advancements in ML/AI.

1. OutlineIntroduction to Few-shot Learning
2. Hands-on Implementation of Different Few-Shot Learning Networks with PyTorch and TensorFlow
3. Introduction of Meta-Learning
4. Hands-on Implementation of Meta-Learning Methods with PyTorch and TensorFlow
5. Application of Meta-Learning

Note: ADaSci Members get 50% discount and Premium Members get 100% discount on the course.