NumPy-Learn, A Homemade Machine Learning Library

Posted on Sun 14 June 2020 in Posts • Tagged with machine learning, python, numpy, deep learning

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


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

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

Continue reading

How to write a decent training loop with enough flexibility.

Posted on Sat 15 June 2019 in Posts • Tagged with deep learning

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


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 …

Continue reading

RiCNN and Rotation Robustness of ConvNets. A Paper Review

Posted on Sat 15 June 2019 in Posts • Tagged with review series, deep learning, computer vision

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 …

Continue reading

Harmonic networks: implementation of paper results

Posted on Sun 10 March 2019 in Posts • Tagged with deep learning, computer vision, work in progress

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


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 …

Continue reading