Projects in Advanced Machine Learning · Quantitative Methods In The Social Sciences
- This class builds on the ML class from QMSS
Fancier models for predictions with tabular, image, audio, video, and time series data.
Better techniques for reducing overfitting & building preprocessing pipelines
More in depth knowledge of Neural Networks. To build more complex NN models for tabular data. To build ML models that have images, videos, and audio files as outputs. ML models for multiple object recognition in frames. Recurrent NN for sequential data. Both tabular and text data. Also applicable to videos and audios. Brief introduction to APIs in AWS and GitHub.
This was a very eye-opening course, coming from a basic machine learning course — we went very deep (pun intended) into different supervised deep learning models over tabular, image and text data.
Various machine learning techniques, insights on how to approach certain types of data (tabular, image, text)
The Professor is great and the course is lighter than Machine Learning. It feels more like a discussion of the frontiers of Machine Learning. Nonetheless, you're going to learn a lot of cool stuff. Definitely recommended if you liked the Machine Learning class!
I think the online modality was handled very well.
I feel like I took away important and valuable machine learning skills that I can apply immediately going forward.
Deep learning techniques and its application