
Home Robots: The Stanford Roadmap Paper
Stanford University researchers, along with industry experts, delve into the evolving landscape of AI and home robotics.

AlexNet: A Revolutionary Deep Learning Architecture
AlexNet is a Image Classification model released in 2012 and the first model to use CNN based Deep Neural Network.

Best Lightweight Computer Vision Models
We introduce the best lightweight computer vision models for fast production, accurate detection, and ease of use.

U-Net: A Comprehensive Guide to Its Architecture and Applications
U-Net is an image segmentation model that features a U-shaped architecture, comprising two main parts: an encoder and decoder.

RetinaNet: Single-Stage Object Detector with Accuracy Focus
RetinaNet is a single-stage object detector that uses Focal Loss and two task-specific sub-networks for object detection.

What is a Decision Tree?
Explore the decision tree algorithm and enhance your Python skills with step-by-step instructions in this comprehensive guide.

Object Localization and Image Localization
Object and image localization in computer vision: enabling machines to detect and accurately pinpoint objects in images.

Concept Drift vs Data Drift: How AI Can Beat the Change
Model drift can degrade a model's performance. Learn about the differences between concept drift vs data drift and mitigation strategies.

Gradient Descent in Computer Vision
Gradient descent is based on a gradual, iterative approach to solving the problem of a function's minimization.

Building Knowledge Graphs With ML: A Technical Guide
Knowledge Graph is a knowledge base that uses graph data structure to store and operate on the data. It powers applications such as Google

MLflow: Simplifying Machine Learning Experimentation
MLflow is an open-source platform that helps streamline the ML process and helps solve incurred challenges with model experimentation.

Getting Started With Kaggle – A Comprehensive Guide
Learn the ins and outs of Kaggle, including finding useful datasets for ML projects and partaking in competitions.