J3 ML/AI Education Experiences

During my excellent Deep Atlas boot camp during the Summer of 2024, I had to complete several project notebooks. Below is a list of some of them:

Shallow Learning

Shallow learning, also known as traditional machine learning, is a type of machine learning model with a simple structure that uses one or a few layers of processing units. These layers perform computations on input data, such as applying transformations or combining information from different sources. Examples of shallow learning models include linear regression, decision trees, logistic regression, and support vector machines.

Classification task type project notebook

Shallow learning, also known as traditional machine learning, is a type of machine learning model with a simple structure that uses one or a few layers of processing units. These layers perform computations on input data, such as applying transformations or combining information from different sources. Examples of shallow learning models include linear regression, decision trees, logistic regression, and support vector machines.

Project Notebook demostrates the following shallow learning algorithms:

• Naive Bayes classifiers
• Linear Support Vector Machine classifier
• XG Boost (eXtreme Gradient Boosting) classifier
• Random Forest classifier
• Logistic Regression Model classifier
• Decision Tree classifier