Deep Learning

Deep Learning

Summer School Lectures: GAN methods for Medical Imaging

This lecture explains deep generative models in medical imaging, covering GANs, VAEs, diffusion models, and real-world medical applications.

Deep Learning

Summer School Lectures: CNN

Video of comprehensive overview of CNN architectures, key concepts, applications, and advanced models like ResNet and EfficientNet.

Data Science

K-means Clustering: Intro with Math and Python

Learn to implement K-Means clustering in Python using customer data, with explanations to understand how the algorithm works.

Data Science

Linear Algebra for Machine Learning: A Python Introduction

Linear algebra provides tools to handle and manipulate complex, high-dimensional data effectively. Key applications include data representation, model training, dimensionality reduction, and neural network operations.

Deep Learning

Machine Learning Programming Skills

Learn foundational machine learning concepts and techniques. This tutorial covers Linear Regression, Logistic Regression, Decision Trees, and K-Nearest Neighbors with practical examples and Python code.

Data Science

Building a Foundation in Data Science

This article illustrates the foundation of data science, covering Basic Data Concepts, Data Collection and Cleaning, and Data Visualization, with illustrations for each section.

Deep Learning

Roadmap for AI and ML for Non Mathematical Background

Roadmap to simplify AI and Machine Learning (ML) for non-math backgrounds, exploring intuitive fundamentals and practical applications.

Deep Learning

Building my own “Comic GPT” using OpenAI’s GPT store .

Build your own

Deep Learning

Python for Deep Learning and Machine Learning.

Learn deep learning with Python from scratch! Start your journey with hands-on coding exercises and overcome your Python limitations for deep learning.

Deep Learning

Pytorch Tutorial Part 2: Model, Training and testing

In this article, we'll learn about building, training, and testing a PyTorch model. Building the model was the hardest part for me. Let's start now with defining, initializing, and connecting layers in the model, followed by training and testing it.

Deep Learning

Pytorch Tutorial Part 1: Dataset and Dataloader

Explore image classification and segmentation with PyTorch, covering dataset setup and data loaders in this beginner-friendly guide.

Deep Learning

Intro to CNN (Convolutional Neural Network)

Learn the basics of Convolutional Neural Networks (CNNs) and how they process images through layers, from input to output.

Deep Learning

Practical Introduction to Deep Learning with PyTorch

A few weeks ago, I was having a chat with my friend when he asked me to teach him Deep Learning in the simplest way possible. The first…

Deep Learning

Explainable YOLOv8 with GRADCAM

Loving YOLOv8 ? It’s great but lacks built-in Explainable AI features like GRAD-CAM. Found a GitHub repo to integrate EigenCAM for better transparency.

Deep Learning

🤗 Huggingface Spaces: Ideal place to show your skills as newbie Data Scientist/ML Engineer

Showcase you AI skills by hosting your models at Huggingface for free

Deep Learning

MultiPlanar UNet: For 3-D Segmentation Tasks - Low Code

Struggling with limited data for 3D medical image segmentation? Try MultiPlanar UNet! Achieved >0.80 dice score on a small knee MRI dataset.