This is a beginner’s guide to gradient boosting in machine learning.
Learn what it is and how to improve its performance with regularization.
AI, artificial intelligence
In this tutorial, we build a deep learning neural network model to classify the sentiment of Yelp reviews.
Following the step-by-step procedures in Python, you’ll see a real life example and learn:
– How to prepare review text data for sentiment analysis, including NLP techniques.
– How to tune the hyperparameters for the machine learning models.
– How to predict sentiment by building an LSTM model in Tensorflow Keras.
– How to evaluate model performance.
– How sample sizes impact the results compared to a pre-trained tool.
We examine the death rate and time to death/recovery distribution of coronavirus with Python.
You’ll see the step-by-step procedures of how to find the parameters of a model that is best fitting the COVID-19 data.
If you want:
– more insights about coronavirus
– or to see an example of hyperparameter tuning/optimization in Python
take a look!