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Updated in [June 30th, 2023]

Michael Carbin will be presenting his seminar on the Lottery Ticket Hypothesis. This seminar will provide an introduction to Neural Networks and discuss the background of Network Pruning. It will also explore the research question, motivation, and questions related to training pruned networks. Additionally, the seminar will cover Iterative Magnitude Pruning, the Lottery Ticket Hypothesis, broader questions, larger-scale settings, scalability challenges, linear mode connectivity, instability, rewinding IMP works, takeaways, our current understanding, implications, and follow-up.

[Applications]
After taking this course, participants should be able to apply the concepts of the Lottery Ticket Hypothesis to their own neural networks. They should be able to use the techniques discussed to prune their networks and reduce training time. Additionally, they should be able to identify scalability challenges and instability issues that may arise when using the Lottery Ticket Hypothesis. Finally, participants should be able to use the techniques discussed to rewind IMP works and improve their networks.

[Career Paths]
One career path that could be recommended to learners of this course is a Machine Learning Engineer. Machine Learning Engineers are responsible for developing and deploying machine learning models and algorithms to solve real-world problems. They must have a strong understanding of mathematics, statistics, and computer science, as well as a deep knowledge of machine learning techniques and frameworks. They must also be able to work with large datasets and have experience with programming languages such as Python, R, and Java.

The development trend for Machine Learning Engineers is to focus on the development of more efficient and accurate models. This includes exploring new techniques such as the Lottery Ticket Hypothesis discussed in this course, as well as developing more efficient algorithms for training and deploying models. Additionally, Machine Learning Engineers must stay up to date with the latest advancements in the field, such as new frameworks and technologies, in order to stay competitive.

[Education Paths]
The recommended educational path for learners interested in the Lottery Ticket Hypothesis is to pursue a degree in Computer Science or Artificial Intelligence. This degree will provide learners with the necessary knowledge and skills to understand the concepts and principles behind the Lottery Ticket Hypothesis. Learners will gain an understanding of neural networks, network pruning, training, and the implications of the Lottery Ticket Hypothesis.

The degree will also provide learners with the opportunity to develop their skills in programming, data analysis, and machine learning. Learners will be able to apply their knowledge to develop and implement algorithms and models to solve real-world problems.

The development trend of this degree is to focus on the application of the Lottery Ticket Hypothesis in larger-scale settings, scalability challenges, linear mode connectivity, and instability. Learners will be able to explore the implications of the Lottery Ticket Hypothesis and develop strategies to address these challenges. They will also be able to develop their skills in rewinding IMP works and apply their knowledge to solve real-world problems.