SignUpIntroduction to Machine Learning for Coders
Other, , Prof. Jeremy Howard
Updated On 02 Feb, 19
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Other, , Prof. Jeremy Howard
Updated On 02 Feb, 19
Learn the most important machine learning models, including how to create them yourself from scratch, as well as key skills in data preparation, model validation, and building data products.
4.1 ( 11 )
In todays lesson well further develop our NLP model by combining the strengths of naive bayes and logistic regression together, creating the hybrid "NB-SVM" model, which is a very strong baseline for text classification.
To do this, well create a new `nn.Module` class in pytorch, and look at what its doing behind the scenes.
In the second half of the lesson well start our study of tabular and relational data using deep learning, by looking at the "Rossmann" Kaggle competition dataset. Today, well start down the feature engineering path on this interesting dataset.
Well look at continuous vs categorical variables, and what kinds of feature engineering can be done for each, with a particular focus on using embedding matrices for categorical variables.
Sam
Sep 12, 2018
Excellent course helped me understand topic that i couldn't while attendinfg my college.
Dembe
March 29, 2019
Great course. Thank you very much.
