In this video, I explain what Hugging Face Transformers and Datasets are and how you can load a model and fine-tune it for text classification. This tutorial is based on Hugging Face course.
I recorded this series for an optional project in the AI course while I was the teaching assistant of this course.
Python, Jupyter Lab, Matplotlib, scikit-learn, pandas, and NumPy are covered in this series.
This series is not for those who are not familiar with programming at all. I recorded this series for computer engineering students familiar with C++ and Java and/or C#.
In this presentation, I explain RNN, its use case, and why we can not always use a feed-forward neural network. I used the slides from a course taught at MIT. The slides were released under MIT License.
I gave this presentation in the Principles of Computational Intelligence class, and all students were familiar with neural networks and feed-forward neural networks.
This presentation was a part of the Electronic Learning course final project. You learn about SVG and how to write one yourself.
You can also watch the video of this presentation on YouTube:
I gave this presentation in the Software Engineering class. In the first part, I talk about free software and GNU/Linux, and in the second part, I talk about Git, how the development of Linux led to creating Git, and how we can use Git.
I gave this presentation in the Internet Engineering class. First, I talk about interfaces and APIs in general and then about RESTful API and its architecture.