The data analysis is documented in Machine_Learning_for_Finance_in_Python_Part_1.ipynb and Machine_Learning_for_Finance_in_Python_Part_2.ipynb. The lecture notes and ...
This sample application shows how to use Amazon Mechanical Turk to create a labeled dataset from raw tweets, and then build a machine learning model using the Amazon Machine Learning API that predicts ...
Preston Fore is a staff writer at Fortune Recommends, covering education and its intersection with business, technology, and beyond. Preston graduated from the University of North Carolina at ...
Beginning with supervised learning, you will review linear and logistic ... learning tasks based on the data’s properties Build and evaluate machine learning models utilizing popular Python libraries ...
Enables readers to understand mathematical concepts behind data engineering and machine learning algorithms and apply them using open-source Python libraries Machine Learning Theory and Applications ...
Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely ...
It will give a strong foundation in two widely used machine learning algorithms: random forests and support vector machines. You will join hands-on coding sessions in Python, using real-world ...
The course also focuses on Python as a programming language, one of the most popular options for numeric computations and machine learning. This will be a hands-on guide on dealing with data for a ...
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