Data Scientist and Machine Learning Engineer. I like to mess with data. email : dhiraj10099@gmail.com
Support vector machine is one of the most popular classical machine learning methods. In this tutorial we'll cover SVM and its implementation in Python.
From bank fraud to preventative machine maintenance, anomaly detection is an incredibly useful and common application of machine learning.
In this article we'll start with an introduction to gradient boosting for regression problems, what makes it so advantageous, and its different parameters. Then we'll implement the GBR model in Python, use it for prediction, and evaluate it.
An introduction to PyTorch, what makes it so advantageous, and how PyTorch compares to TensorFlow and Scikit-Learn. Then we'll look at how to use PyTorch by building a linear regression model and using it to make predictions.
