Introduction to Deep Learning
Deep Learning is subset of machine learning focused on extracting patterns from data using neural networks and use those patterns to inform the learning tasks.
Imagery and Remote Sensing
Learn the basics of observing and understanding our planet with the help of Arc Gis.
Convolutional Neural Networks for Visual Recognition
This lecture collection is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification.
Object Detection on Custom Dataset with YOLO - Fine-Tuning with PyTorch and Python Tutorial
Fine-tune YOLO v5 for custom object detection using PyTorch. Learn model installation, training, evaluation, and application on a clothing dataset.
Stable Diffusion Prompt Tutorial
Explore OpenArt's prompt book for Stable Diffusion, covering format, modifiers, magic words, and parameters to enhance AI image generation skills.
Stanford Seminar - Google's Multilingual Neural Machine Translation System
Exploring Google's Multilingual Neural Machine Translation system, its ability for zero-shot translation, and the potential existence of an interlingua in language processing.
Cognitive Robotics, Spring 2016
This is an advanced lecture series from MIT 16.412 Cognitive Robotics of Spring 2016, led by MIT students.
Deep Learning for Computer Vision
Comprehensive exploration of deep learning techniques for computer vision, covering classification, neural networks, CNNs, object detection, 3D vision, and generative models.
Deep Learning Powered Faster and Low-Dose Imaging, MR, PET and Beyond
Explore cutting-edge deep learning applications for accelerated, low-dose medical imaging across MR, PET, and other modalities, enhancing diagnostic efficiency and patient safety.
Deep Learning Lecture Series
Comprehensive lecture series covering key deep learning topics, from fundamentals to advanced concepts, including neural networks, computer vision, NLP, and ethical considerations.
Artificial Intelligence Safety and Security - Roman V. Yampolskiy, PhD
Explore AI's impact on cybersecurity, its potential risks and benefits, and strategies for ensuring AI safety and ethical development in this thought-provoking talk by Dr. Yampolskiy.
DreamBooth: Personalized Text-to-Image Generation - Lecture 10
Explore DreamBooth's innovative approach to AI-generated imagery, including unique identifiers, recontextualization, and artistic renditions. Gain insights into its capabilities and limitations.
Deep Learning for Visual Computing
Comprehensive exploration of deep learning techniques for visual computing, covering neural networks, autoencoders, and CNNs with hands-on implementations using Python and popular datasets.
CUDA Crash Course
Comprehensive introduction to CUDA programming, covering vector operations, matrix multiplication, memory optimization, and performance tuning for GPU-accelerated computing.
Face Detection with OpenCV in Python - OpenCV Python Tutorial for Beginners
Learn face detection using OpenCV in Python, covering concepts from basic detection to deep learning applications. Gain practical skills through hands-on tutorials and real-world examples.
Z-Transform
Comprehensive exploration of Z-Transform concepts, including inverse methods, properties, and practical applications, with additional insights on CSIR NET exam preparation.
Fluid Dynamics
Explore machine learning applications in fluid dynamics, from turbulence modeling to control strategies, with a focus on data-driven approaches and advanced computational techniques.
Mathematics for Data Science - Essential Math for Machine Learning
Explore essential math for data science, including probability, statistics, machine learning, and deep learning. Learn through real-world case studies and gain insights into the crucial role of mathematics in data analysis.
Deep Learning
Explore deep learning fundamentals, computer vision, TensorFlow, Keras, transfer learning, and advanced topics like TPUs in this comprehensive introduction to neural networks.
Image Processing in MATLAB
Learn essential image processing techniques in MATLAB, from basic operations to advanced filters and edge detection. Gain practical skills for manipulating, analyzing, and enhancing digital images efficiently.
Deep Learning Using Matlab
Explore deep learning concepts and implement neural networks, including CNNs, using MATLAB for practical applications in image classification and beyond.