Marktechpost

NOVEMBER 18, 2024

Utilizing a Graph Neural Network (GNN) for predicting compound effectiveness, VirtuDockDL achieved 99% accuracy on the HER2 dataset, surpassing tools like DeepChem and AutoDock Vina. In conclusion, VirtuDockDL is a new Python-based web platform designed to streamline drug discovery using deep learning.

Deep Learning 81

Deep Learning Neural Network Python Automation 81

NVIDIA

JULY 3, 2024

How It All BeGAN GANs are deep learning models that involve two complementary neural networks: a generator and a discriminator. These neural networks compete against each other. As its neural networks keep challenging each other, GANs get better and better at making realistic-looking samples.

Generative AI 120

Generative AI Neural Network AI AI 120

Unite.AI

JUNE 21, 2024

The Rise of CUDA-Accelerated AI Frameworks GPU-accelerated deep learning has been fueled by the development of popular AI frameworks that leverage CUDA for efficient computation. NVIDIA TensorRT , a high-performance deep learning inference optimizer and runtime, plays a vital role in accelerating LLM inference on CUDA-enabled GPUs.

Deep Learning 130

Deep Learning Neural Network Convolutional Neural Networks Large Language Models 130

PyImageSearch

OCTOBER 28, 2024

Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Steps Next Steps Citation Information NeRFs Explained: Goodbye Photogrammetry? In this blog post, you will learn about 3D Reconstruction. How Do NeRFs Work?

Explainability 94

Explainability Neural Network Computer Vision Deep Learning 94

NVIDIA

OCTOBER 11, 2024

Teens gleefully downloaded Britney Spears and Eminem on Napster. Deep learning — a software model that relies on billions of neurons and trillions of connections — requires immense computational power. In 1999, fans lined up at Blockbuster to rent chunky VHS tapes of The Matrix. This marked a seismic shift in technology.

Neural Network 142

Neural Network Deep Learning AI AI 142

PyImageSearch

FEBRUARY 6, 2023

Furthermore, this tutorial aims to develop an image classification model that can learn to classify one of the 15 vegetables (e.g., If you are a regular PyImageSearch reader and have even basic knowledge of Deep Learning in Computer Vision, then this tutorial should be easy to understand. tomato, brinjal, and bottle gourd).

Auto-classification 131

Auto-classification Computer Vision Neural Network Deep Learning 131

Dlabs.ai

JUNE 19, 2020

If you Google ‘ what’s needed for deep learning ,’ you’ll find plenty of advice that says vast swathes of labeled data (say, millions of images with annotated sections) are an absolute must. You may well come away thinking, deep learning is for ‘superhumans only’ — superhumans with supercomputers. Sounds interesting?

Deep Learning 52

Deep Learning Neural Network Machine Learning Computer Vision 52

Unite.AI

SEPTEMBER 14, 2023

Even today, a vast chunk of machine learning and deep learning techniques for AI models rely on a centralized model that trains a group of servers that run or train a specific model against training data, and then verifies the learning using validation or training dataset.

AI 319

AI AI Algorithm Artificial Intelligence 319

Flipboard

MARCH 6, 2023

Jump Right To The Downloads Section Triplet Loss with Keras and TensorFlow In the first part of this series, we discussed the basic formulation of a contrastive loss and how it can be used to learn a distance measure based on similarity. Looking for the source code to this post? Or has to involve complex mathematics and equations?

Computer Vision 144

Computer Vision Deep Learning Neural Network Artificial Intelligence 144

Flipboard

APRIL 17, 2023

Jump Right To The Downloads Section Learning JAX in 2023: Part 3 — A Step-by-Step Guide to Training Your First Machine Learning Model with JAX We conclude our “ Learning JAX in 2023 ” series with a hands-on tutorial. The missing piece of training a neural network is the update_step.

Machine Learning 139

Machine Learning Computer Vision Neural Network Deep Learning 139

PyImageSearch

DECEMBER 19, 2022

Table of Contents OAK-D: Understanding and Running Neural Network Inference with DepthAI API Introduction Configuring Your Development Environment Having Problems Configuring Your Development Environment? Start by accessing the “Downloads” section of this tutorial to retrieve the source code and example images.

Neural Network 52

Neural Network Computer Vision Deep Learning Metadata 52

PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

Convolutional Neural Networks 115

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 115

Kavita Ganesan

JANUARY 27, 2022

This is a guest post from Andrew Ferlitsch, author of Deep Learning Patterns and Practices. It provides an introduction to deep neural networks in Python. Andrew is an expert on computer vision, deep learning, and operationalizing ML in production at Google Cloud AI Developer Relations.

Neural Network 52

Neural Network Python Deep Learning Convolutional Neural Networks 52

Viso.ai

DECEMBER 10, 2023

Image recognition with deep learning is a key application of AI vision and is used to power a wide range of real-world use cases today. I n past years, machine learning, in particular deep learning technology , has achieved big successes in many computer vision and image understanding tasks.

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

PyImageSearch

MAY 8, 2023

What is the reason for such injustice, and how can we exploit that in machine learning? To learn how to understand and correctly interpret causality, just keep reading. Jump Right To The Downloads Section Introduction to Causality in Machine Learning So, what does causal inference mean? Let’s find out.

Machine Learning 107

Machine Learning Computer Vision Deep Learning Neural Network 107

PyImageSearch

FEBRUARY 20, 2023

Jump Right To The Downloads Section Learning JAX in 2023: Part 1 — The Ultimate Guide to Accelerating Numerical Computation and Machine Learning ?? Introduction As deep learning practitioners, it can be tough to keep up with all the new developments. Automatic Differentiation is at the very heart of Deep Learning.

Machine Learning 109

Machine Learning Deep Learning Computer Vision Neural Network 109

PyImageSearch

SEPTEMBER 23, 2024

Home Table of Contents Deploying a Vision Transformer Deep Learning Model with FastAPI in Python What Is FastAPI? You’ll learn how to structure your project for efficient model serving, implement robust testing strategies with PyTest, and manage dependencies to ensure a smooth deployment process. Testing main.py Testing main.py

Deep Learning 60

Deep Learning Python Computer Vision Software Development 60

Flipboard

JULY 10, 2023

An autoencoder is an artificial neural network used for unsupervised learning tasks (i.e., Figure 5: Architecture of Convolutional Autoencoder for Image Segmentation (source: Bandyopadhyay, “Autoencoders in Deep Learning: Tutorial & Use Cases [2023],” V7Labs , 2023 ). What Are Autoencoders? That’s not the case.

Computer Vision 132

Computer Vision Deep Learning Neural Network Machine Learning 132

PyImageSearch

APRIL 24, 2023

This tutorial is primarily for developers who want to accelerate their deep learning models with PyTorch 2.0. In this series, you will learn about Accelerating Deep Learning Models with PyTorch 2.0. TorchDynamo and TorchInductor (primarily for developers) (this tutorial) To learn what’s behind PyTorch 2.0,

Neural Network 95

Neural Network Deep Learning Computer Vision Python 95

Viso.ai

DECEMBER 1, 2023

AI vs. Machine Learning vs. Deep Learning First, it is important to gain a clear understanding of the basic concepts of artificial intelligence types. We often find the terms Artificial Intelligence and Machine Learning or Deep Learning being used interchangeably. Get the Whitepaper or a Demo.

AI Modeling 98

AI Modeling Neural Network Computer Vision Deep Learning 98

AWS Machine Learning Blog

MARCH 8, 2023

This post shows a way to do this using Snowflake as the data source and by downloading the data directly from Snowflake into a SageMaker Training job instance. We create a custom training container that downloads data directly from the Snowflake table into the training instance rather than first downloading the data into an S3 bucket.

ML 136

ML Python Machine Learning Neural Network 136

Viso.ai

DECEMBER 20, 2023

Modern vision systems use algorithms based on machine learning, deep learning especially, that need to be trained on images annotated by humans (supervised learning). A deep learning model trained for AI vision inspection in Manufacturing Where can I try CVAT?

Computer Vision 98

Computer Vision Neural Network Deep Learning Machine Learning 98

Unite.AI

DECEMBER 19, 2023

Carl Froggett, is the Chief Information Officer (CIO) of Deep Instinct , an enterprise founded on a simple premise: that deep learning , an advanced subset of AI, could be applied to cybersecurity to prevent more threats, faster. DL is built on a neural network and uses its “brain” to continuously train itself on raw data.

Neural Network 147

Neural Network Deep Learning Metadata ML 147

Flipboard

FEBRUARY 13, 2023

Specifically, we will discuss the following in detail: Positive and Negative data samples required to train a network with contrastive loss Specific data preprocessing techniques (e.g., We tried to understand how these losses can help us learn a distance measure based on similarity. In Deep Learning, we need to train Neural Networks.

Computer Vision 145

Computer Vision Deep Learning Neural Network Auto-complete 145

PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate. Diabetic Retinopathy, see Figure 9 ).

Computer Vision 52

Computer Vision Deep Learning Neural Network Machine Learning 52

AWS Machine Learning Blog

MAY 1, 2024

AWS Trainium instances for training workloads SageMaker ml.trn1 and ml.trn1n instances, powered by Trainium accelerators, are purpose-built for high-performance deep learning training and offer up to 50% cost-to-train savings over comparable training optimized Amazon Elastic Compute Cloud (Amazon EC2) instances.

Auto-complete 126

Auto-complete ML Deep Learning Generative AI 126

PyImageSearch

JANUARY 9, 2023

To learn how to develop Face Recognition applications using Siamese Networks, just keep reading. Jump Right To The Downloads Section Face Recognition with Siamese Networks, Keras, and TensorFlow Deep learning models tend to develop a bias toward the data distribution on which they have been trained.

Computer Vision 88

Computer Vision Deep Learning Neural Network Algorithm 88

Mlearning.ai

JANUARY 27, 2023

Save this blog for comprehensive resources for computer vision Source: appen Working in computer vision and deep learning is fantastic because, after every few months, someone comes up with something crazy that completely changes your perspective on what is feasible. A dataset is a group of samples (in this case, photos or videos).

Computer Vision 98

Computer Vision Deep Learning Python Neural Network 98

PyImageSearch

OCTOBER 14, 2024

The second blog post will introduce you to NeRFs , the neural network solution. Neural Radiance Fields have been about turning an image into a 3D model… but using Deep Learning! And in an upcoming post, we’ll dive into the 5 main steps to build neural radiance fields! Have you felt it? What's next?

Explainability 113

Explainability Computer Vision Deep Learning Algorithm 113

Mlearning.ai

MAY 16, 2023

Deployment of deep neural network on mobile phone. (a) Introduction As more and more deep neural networks, like CNNs, Transformers, and Large Language Models (LLMs), generative models, etc., to boost the usages of the deep neural networks in our lives. " #include "inference.h"

Neural Network 98

Neural Network Convolutional Neural Networks Deep Learning Inference Engine 98

AWS Machine Learning Blog

SEPTEMBER 20, 2023

AWS provides Deep Learning Containers (DLCs) for popular ML frameworks such as PyTorch, TensorFlow, and Apache MXNet, which you can use with SageMaker for training and inference. When model training is complete, we use the Open Neural Network Exchange (ONNX) runtime library to export the PyTorch model as an ONNX model.

ML 133

ML Python Deep Learning Machine Learning 133

PyImageSearch

DECEMBER 9, 2024

And in the 2nd blog of this series , you were introduced to NeRFs, which is 3D Reconstruction via Neural Networks, projecting points in the 3D space. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? So, whats the big idea behind Gaussian Splatting?

Computer Vision 95

Computer Vision Deep Learning Explainability Algorithm 95

Towards AI

NOVEMBER 6, 2024

But how can we harness machine learning for something as niche as rice classification? Well, this is where PyTorch, a powerful deep learning library, steps in. Today, I’ll guide you through creating a Convolutional Neural Network (CNN) using PyTorch to classify rice varieties based on images.

Convolutional Neural Networks 133

Convolutional Neural Networks Neural Network Deep Learning Machine Learning 133

PyImageSearch

JUNE 26, 2023

Starting with the input image , which has 3 color channels, the authors employ a standard Convolutional Neural Network (CNN) to create a lower-resolution activation map. The feed-forward neural network (FFN) predicts the bounding box’s normalized center coordinates, height, and width with respect to the input image.

Convolutional Neural Networks 86

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 86

Explosion

OCTOBER 18, 2016

The custom pipelines are particularly exciting, because they let you hook your own deep learning models into spaCy. How to add sentiment analysis to spaCy with an LSTM model using Keras There are lots of great open-source libraries for researching, training and evaluating neural networks. Theano is also supported.

Deep Learning 52

Deep Learning Neural Network NLP Python 52

Towards AI

AUGUST 28, 2023

Apply these concepts to solve real-world industry problems in deep learning Taking a step away from classical machine learning (ML), embeddings are at the core of most deep learning (DL) use cases. You can download the images here [4]. You can download the data here (product images by [5]).

Deep Learning 98

Deep Learning Computer Vision Neural Network Natural Language Processing 98

Flipboard

JULY 31, 2023

Object detection works by using machine learning or deep learning models that learn from many examples of images with objects and their labels. In the early days of machine learning, this was often done manually, with researchers defining features (e.g., Object detection is useful for many applications (e.g.,

Machine Learning 123

Machine Learning Computer Vision Deep Learning Convolutional Neural Networks 123