Category Archives: Deep Learning
From Proof-of-Concept to Real-World Impact: How to Successfully Deploy Machine Learning Models
Machine learning (ML) has revolutionized industries by unlocking the potential to automate tasks, generate new insights from data, and create entirely new product experiences. Yet, many practitioners and aspiring ML engineers discover a significant gap between training a great model in a lab or a Jupyter Notebook and actually running that model in production to solve real…
MultiClass Classification
Image classification is a type of supervised machine learning task where the goal is to sort images in a dataset into their appropriate categories or labels. For instance, classifying different types of dog breeds from images is a common example of image classification. This is referred to as “multi-class classification” since we’re sorting images into…
Digit Recognition: Kaggle Challenge
Digit recognition is a classic problem in the field of computer vision, with a wide range of practical applications such as optical character recognition (OCR), handwriting recognition, and digit-based security systems. The challenge in digit recognition is to train a machine learning model that can accurately classify handwritten digits from a given dataset. Recently, the…
Fully Connected Neural Network
We will explore the fascinating field of deep learning in this blog post. The primary neural network configuration we use today, feed-forward networks, will be the subject of our attention today. We will investigate the key ideas and theories that have shaped the deep learning field. In the upcoming posts, we’ll talk about the initial…