Implementing Fully Convolutional Networks (FCNs) from scratch in Keras and TensorFlow (Build image segmentation model from scratch) Paid Members Public
In 2014, Jonathan Long, Evan Shelhamer, and Trevor Darrell proposed solving image segmentation problems using Fully Convolutional Neural Networks(FCNs). FCNs have no fully connected layers. Image segmentation involves making a prediction for each pixel in an image. FCNs can accept images of any size because they don't
Entropy, information gain, and Gini impurity(Decision tree splitting criteria) Paid Members Public
Decision trees are supervised machine-learning models used to solve classification and regression problems. They help to make decisions by breaking down a problem with a bunch of if-else-then-like evaluations that result in a tree-like structure. For quality and viable decisions to be made, a decision tree builds itself by splitting
Decision Trees and Random Forests(Building and optimizing decision tree and random forest models) Paid Members Public
In the modern world, so much data is present on the internet. Organizations need efficient and rigorous algorithms to handle these huge chunks of data, make practical analyses, and provide appropriate decisions relevant to maximizing their profits and market presence. There are such algorithms commonly used today for decision-making processes.
How to become a Kaggle Competitions Grandmaster Paid Members Public
writtencast 001 - Shujun He In this inaugural interview of the writtencast, I am joined by Shujun He. Shujun is a P.hD. student at Texas A&M University and a Kaggle Competitions Grandmaster. To become a Kaggle Competitions Grandmaster you need 5 gold medals and at least one
Gradio tutorial (Build machine learning applications) Paid Members Public
You have built your optimally performing machine learning model. What next? This tutorial explores the use of Gradio in building machine learning applications. What is Gradio? Gradio is an open-source Python package that allows you to quickly create easy-to-use, customizable UI components for your ML model, any API, or even
Free data science course Paid Members Public
Join my free data science and machine learning email course with Python. Each day I will share a new lesson and provide code examples and notebooks to help you in your data science journey. The course covers beginner to advanced concepts in data science and machine learning. I will provide
Object detection with Vision Transformer for Open-World Localization(OWL-ViT) Paid Members Public
Convolutional neural networks have been the primary networks applied in objection detection. Recently, Transformers have gained popularity in natural language processing and computer vision. In this article, we explore the use of the OWL-ViT in object detection. Let’s get started. What is a Vision Transformer? Transformers have been widely
Logistic regression in Python with Scikit-learn Paid Members Public
In linear regression, we tried to understand the relationship between one or more predictor variables and a continuous response variable. This article will explore logistic regression, where the response variable will be discrete or categorical. What is classification? Classification is a supervised machine learning problem of predicting which category or
