We live in a far from perfect world, and many times, the data we need for training our machine learning models isn’t already present in some Internet dataset. As a result, it’s quite important for a machine learning developer to understand how exactly they can construct their own datasets in such situations. In today’s post, […]
Category: Neural Networks
Tensors & Machine Learning
When it comes to building neural network models, there’s a lot of factors to consider such as hyperparameter tuning, model architecture, whether to use a pre-trained model or not, and so on and so forth. While it’s true that these are all important aspects to consider, I would argue that proper understanding of data representations […]
From Artificial Intelligence to Deep Learning
Deep learning is one of the hottest topics in today’s digital world. Everyone wants to know just how much potential this tool has in terms of revolutionizing technology and whether or not it will be able to introduce utopian elements such as intelligent autonomous systems (chatbots, self-driving cars, etc.). However, before one delves into the […]
Hyper Parameter Tuning… What’s That?
The Rise of Deep Learning In the span of a few years, deep learning has taken the world by storm and has established itself as a very powerful tool under many applications such as image classification, anomaly detection, natural language processing, and much more. This became possible especially through the emergence of deep neural networks, […]
Predicting Suicide Rates Using Linear Regression
Hi everyone! I’m taking an online deep learning with PyTorch course, which has turned out to be a really enjoyable experience. That being said, for our second assignment, our core focus was on building a Linear Regression model that predicts insurance charges. I sure finished that assignment. However, to spice things up a bit, I […]