Unite.AI

APRIL 15, 2025

Can you explain how TheStage AI automates this process and why its a game-changer? Instead of applying the same algorithm to the entire neural network, ANNA breaks it down into smaller layers and decides which algorithm to apply for each part to deliver desired compression while maximizing models quality.

Neural Network 120

Neural Network Algorithm Automation AI 120

Marktechpost

MAY 8, 2024

Over the past decade, advancements in deep learning and artificial intelligence have driven significant strides in self-driving vehicle technology. Deep learning and AI technologies play crucial roles in both modular and End2End systems for autonomous driving. Classical methodologies for these tasks are also explored.

Deep Learning 121

Deep Learning Neural Network Data Scarcity Natural Language Processing 121

Unite.AI

MARCH 20, 2025

I am lucky to run a company that gives me a deep sense of purpose and allows me to work with an incredibly talented team from diverse backgrounds and disciplines. I then worked as an algorithms engineer and moved on to product management. We hired two engineers and developed our first algorithm for prostate cancer detection.

Convolutional Neural Networks 144

Convolutional Neural Networks Algorithm Explainability Neural Network 144

IBM Journey to AI blog

AUGUST 9, 2024

Most generative AI models start with a foundation model , a type of deep learning model that “learns” to generate statistically probable outputs when prompted. Predictive AI blends statistical analysis with machine learning algorithms to find data patterns and forecast future outcomes.

Generative AI 301

Generative AI Explainability AI AI 301

PyImageSearch

DECEMBER 9, 2024

In this tutorial, you will learn about 3D Gaussian Splatting. This lesson is the last of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion NeRFs Explained: Goodbye Photogrammetry? this tutorial) To learn more about 3D Gaussian Splatting, just keep reading.

Computer Vision 110

Computer Vision Deep Learning Explainability Algorithm 110

Marktechpost

MAY 14, 2024

Deep learning is crucial in today’s age as it powers advancements in artificial intelligence, enabling applications like image and speech recognition, language translation, and autonomous vehicles. Additionally, it offers insights into the diverse range of deep learning techniques applied across various industrial sectors.

Neural Network 108

Neural Network Deep Learning Computer Vision Python 108

Towards AI

FEBRUARY 3, 2024

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. The truth is, I couldn’t find anything.

Explainability 126

Explainability Explainable AI Neural Network Algorithm 126

Towards AI

SEPTEMBER 10, 2023

What I’ve learned from the most popular DL course Photo by Sincerely Media on Unsplash I’ve recently finished the Practical Deep Learning Course from Fast.AI. So you definitely can trust his expertise in Machine Learning and Deep Learning. Luckily, there’s a handy tool to pick up Deep Learning Architecture.

Deep Learning 124

Deep Learning Neural Network ML Computer Vision 124

PyImageSearch

DECEMBER 23, 2024

These scenarios demand efficient algorithms to process and retrieve relevant data swiftly. This is where Approximate Nearest Neighbor (ANN) search algorithms come into play. ANN algorithms are designed to quickly find data points close to a given query point without necessarily being the absolute closest.

Computer Vision 112

Computer Vision Algorithm Deep Learning Metadata 112

Marktechpost

MARCH 26, 2024

Deep learning models have recently gained significant popularity in the Artificial Intelligence community. In order to address these challenges, a team of researchers has introduced DomainLab, a modular Python package for domain generalization in deep learning. If you like our work, you will love our newsletter.

Deep Learning 127

Deep Learning Python Neural Network Artificial Intelligence 127

PyImageSearch

OCTOBER 28, 2024

Home Table of Contents NeRFs Explained: Goodbye Photogrammetry? 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? How Do NeRFs Work?

Explainability 106

Explainability Neural Network Computer Vision Deep Learning 106

Marktechpost

JUNE 16, 2024

Topological Deep Learning (TDL) advances beyond traditional GNNs by modeling complex multi-way relationships, unlike GNNs that only capture pairwise interactions. Topological Neural Networks (TNNs), a subset of TDL, excel in handling higher-order relational data and have shown superior performance in various machine-learning tasks.

Deep Learning 129

Deep Learning Neural Network Machine Learning Explainability 129

PyImageSearch

OCTOBER 14, 2024

This blog post is the 1st of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion (this blog post) 3D Reconstruction: Have NeRFs Removed the Need for Photogrammetry? To learn about 3D Reconstruction, just keep reading. 3D Gaussian Splatting: The End Game of 3D Reconstruction?

Explainability 118

Explainability Computer Vision Deep Learning Algorithm 118

How to Learn Machine Learning

APRIL 8, 2025

TLDR: In this article we will explore machine learning definitions from leading experts and books, so sit back, relax, and enjoy seeing how the field’s brightest minds explain this revolutionary technology! This focus on examples highlights the data-driven nature of machine learning as opposed to rule-based programming.

Machine Learning 76

Machine Learning Deep Learning Artificial Intelligence Artificial Intelligence 76

Unite.AI

NOVEMBER 6, 2023

Traditional machine learning is a broad term that covers a wide variety of algorithms primarily driven by statistics. The two main types of traditional ML algorithms are supervised and unsupervised. These algorithms are designed to develop models from structured datasets. K-means Clustering. K-means Clustering.

Machine Learning 201

Machine Learning Neural Network Deep Learning Convolutional Neural Networks 201

AI Weekly

OCTOBER 12, 2023

techspot.com Applied use cases Study employs deep learning to explain extreme events Identifying the underlying cause of extreme events such as floods, heavy downpours or tornados is immensely difficult and can take a concerted effort by scientists over several decades to arrive at feasible physical explanations.

Robotics 264

Robotics Large Language Models Deep Learning Artificial Intelligence 264

Marktechpost

APRIL 24, 2024

Explainable AI (XAI) aims to balance model explainability with high learning performance, fostering human understanding, trust, and effective management of AI partners. ELI5 is a Python package that helps debug machine learning classifiers and explain their predictions.

Explainable AI 116

Explainable AI Explainability Neural Network Data Scientist 116

Marktechpost

OCTOBER 8, 2023

The researchers emphasize that this approach of explainability examines an AI’s full prediction process from input to output. The research group has already created techniques for using heat maps to demonstrate how AI algorithms make judgments. If you like our work, you will love our newsletter. We are also on WhatsApp.

Deep Learning 140

Deep Learning Neural Network Explainability Artificial Intelligence 140

Towards AI

NOVEMBER 19, 2023

Photo by Pietro Jeng on Unsplash Deep learning is a type of machine learning that utilizes layered neural networks to help computers learn from large amounts of data in an automated way, much like humans do. Loss functions guide learning by measuring errors. Activation functions introduce non-linear patterns.

Deep Learning 126

Deep Learning Neural Network Natural Language Processing Machine Learning 126

Unite.AI

DECEMBER 1, 2023

Machine learning , a subset of AI, involves three components: algorithms, training data, and the resulting model. An algorithm, essentially a set of procedures, learns to identify patterns from a large set of examples (training data). The culmination of this training is a machine-learning model.

LLM 261

LLM Machine Learning Explainability Algorithm 261

The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

Deep Learning 111

Deep Learning Neural Network Convolutional Neural Networks Data Scientist 111

Unite.AI

FEBRUARY 25, 2025

As AI systems increasingly power mission-critical applications across industries such as finance, defense, healthcare, and autonomous systems, the demand for trustworthy, explainable, and mathematically rigorous reasoning has never been higher. Imandra is dedicated to bringing rigor and governance to the world's most critical algorithms.

Automation 100

Automation Neural Network Explainability AI 100

AssemblyAI

NOVEMBER 21, 2022

At the bedrock of the Deep Learning that powers incredible technologies like text-to-image models lies matrix multiplication. Regardless of the specific architecture employed, (nearly) every Neural Network relies on efficient matrix multiplication to learn and infer.

Explainability 130

Explainability Neural Network Algorithm Deep Learning 130

PyImageSearch

JANUARY 20, 2025

This algorithm takes advantage of the frequency of occurrence of each data item (e.g., Huffman encoding is a prime example of a lossless compression algorithm. Huffman encoding is a widely used lossless data compression algorithm. The following code snippet creates the Huffman tree, as explained above.

Computer Vision 111

Computer Vision Deep Learning Explainability Algorithm 111

PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. As soon as the system adapts to human wants, it automates the learning process accordingly.

Computer Vision 105

Computer Vision Deep Learning Neural Network Artificial Intelligence 105

Marktechpost

AUGUST 15, 2023

Data may be viewed as having a structure in various areas that explains how its components fit together to form a greater whole. Most current deep-learning models make no explicit attempt to represent the intermediate structure and instead seek to predict output variables straight from the input.

Deep Learning 98

Deep Learning Algorithm Explainability Machine Learning 98

AI Weekly

APRIL 11, 2024

And this is particularly true for accounts payable (AP) programs, where AI, coupled with advancements in deep learning, computer vision and natural language processing (NLP), is helping drive increased efficiency, accuracy and cost savings for businesses. Answering them, he explained, requires an interdisciplinary approach.

Robotics 264

Robotics Artificial Intelligence Artificial Intelligence Data Drift 264

Pickl AI

APRIL 9, 2025

Summary: Artificial Intelligence (AI) and Deep Learning (DL) are often confused. AI vs Deep Learning is a common topic of discussion, as AI encompasses broader intelligent systems, while DL is a subset focused on neural networks. Is Deep Learning just another name for AI? Is all AI Deep Learning?

Deep Learning 52

Deep Learning Artificial Intelligence Artificial Intelligence Explainability 52

Towards AI

FEBRUARY 6, 2025

to Artificial Super Intelligence and black box deep learning models. It details the underlying Transformer architecture, including self-attention mechanisms, positional embeddings, and feed-forward networks, explaining how these components contribute to Llamas capabilities. Enjoy the read!

Deep Learning 79

Deep Learning Computer Vision Large Language Models Explainability 79

Unite.AI

NOVEMBER 20, 2024

Teaching radiology residents has sharpened my ability to explain complex ideas clearly, which is key when bridging the gap between AI technology and its real-world use in healthcare. AI algorithms can serve as a constant teacher and assistant, decreasing the cognitive load and leveling up all providers to provide world-class care.

Robotics 130

Robotics AI AI Computer Vision 130

Marktechpost

MARCH 28, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

Artificial Intelligence 142

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 142

Unite.AI

NOVEMBER 25, 2024

I'll explain each pattern with practical AI use cases and Python code examples. Let’s explore some key design patterns that are particularly useful in AI and machine learning contexts, along with Python examples. retraining models, swapping algorithms). This is especially useful in AI systems where the same process (e.g.,

Python 144

Python LLM AI Engineer AI 144

Analytics Vidhya

JUNE 18, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon This article explains the problem of exploding and vanishing gradients while. The post The Challenge of Vanishing/Exploding Gradients in Deep Neural Networks appeared first on Analytics Vidhya.

Neural Network 329

Neural Network Data Science Explainability Algorithm 329

Unite.AI

APRIL 9, 2024

These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Explainability is essential for accountability, fairness, and user confidence. Explainability also aligns with business ethics and regulatory compliance.

Composite AI 176

Composite AI Explainability Black Box AI Explainable AI 176

Marktechpost

NOVEMBER 20, 2024

Others have proposed a hybrid network intrusion detection system integrating convolutional neural networks (CNN), fuzzy C-means clustering, genetic algorithm, and a bagging classifier. By hybridizing optimization techniques with deep belief networks, the method aims to enhance DDoS attack detection accuracy, speed, and scalability.

Deep Learning 82

Deep Learning Convolutional Neural Networks Neural Network Algorithm 82

PyImageSearch

APRIL 7, 2025

Singular Value Decomposition Singular Value Decomposition (SVD) is a popular algorithm used to diagonalize a matrix of an arbitrary shape. Power Iteration Algorithm Given a matrix of size , the power iteration algorithm to obtain , , and involves the following steps.

Algorithm 101

Algorithm Explainability Computer Vision Deep Learning 101

IBM Journey to AI blog

JANUARY 10, 2024

AI operates on three fundamental components: data, algorithms and computing power. Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models. What is artificial intelligence and how does it work?

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Artificial Intelligence Artificial Intelligence Neural Network Algorithm 229