In this post, I expand on a little class/self-teaching project that I did during the Spring 2020 semester.

NumPy-Learn: A Homemade Machine Learning Library

Organization

In this section we will discuss the main organization of the library:

• How the layers are built
• How loss functions work
• How a stochastic …

In this post, I put together an interesting example of what to do with imbalanced datasets and why precision and recall matter.

Introduction

The following is part of a Machine learning assignment I had to do while at CUNY. This particular example illustrates quite well the importance of understanding various …

In this post I wanted to describe a simple application of a linear least squares method to a problem of data classification. It is a naive approach and is unlikely to beat more sophisticated techniques like Logistic Regression, for instance.

Imports

Some imports we are going to need for this …

In this post, I briefly describe my experience in setting up training with PyTorch.

Introduction

PyTorch is an extremely useful and convenient framework for deep learning. When it comes to working on a deep learning project, I am more comfortable with PyTorch rather than TensorFlow.

In this quick post, I …

Lately, I have been reading more papers on modern advances in deep learning in order to get a clear view of what problem I want to focus on during my PhD research.

There is a lot of information to process and an incredible amount of papers are being published from …

A little overview of what I talked about at CUNY CSI Science Day.

During the Science Day at the CUNY College of Staten Island, I presented a gentle introduction to area of computer vision with fun examples and research results to visiting middle and high school students.

It was a …

I implement an interesting result from a recent paper on convolutional neural networks.

Introduction

In this post I will briefly discuss my implementation of a model introduced in this paper.

In short, the authors suggest using predefined filters in a convolutional network based on Discrete Cosine Transform.

I used PyTorch …

A simple function that can be used to justify image quality and control enhancement.

Introduction

One difficult thing about image enhancement is to actually measure the level of image quality which is quite a subjective task. On the one hand, each individual can perceive the image quality according to their …

Let's talk about all things image enhancement, what it is, why it is necessary and how do wavelets play a big part in it!

Introduction

Enhancement of images is an important preprocessing step in any image related system. Getting rid of noise, brightening, extraction of details - all of this helps …