ML Review

MARCH 31, 2019

Up to this point, machine learning algorithms simply didn’t work well enough for anyone to be surprised when it failed to do the right thing. We start with an image of a panda, which our neural network correctly recognizes as a “panda” with 57.7% This is, clearly, an optical illusion — but for the neural network.

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Unite.AI

JULY 24, 2024

Over the past decade, advancements in machine learning, Natural Language Processing (NLP), and neural networks have transformed the field. In 2017, Apple introduced Core ML , a machine learning framework that allowed developers to integrate AI capabilities into their apps. Notable acquisitions include companies like Xnor.a

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Viso.ai

DECEMBER 3, 2023

This article will provide an introduction to object detection and provide an overview of the state-of-the-art computer vision object detection algorithms. The recent deep learning algorithms provide robust person detection results. Detecting people in video streams is an important task in modern video surveillance systems.

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Unite.AI

MAY 8, 2024

He began his career at Yandex in 2017, concurrently studying at the Yandex School of Data Analysis. During my school years, I spent a lot of time studying math, probability theory, and statistics, and got an opportunity to play with classical machine learning algorithms such as linear regression and KNN.

Machine Learning 298

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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Towards AI

AUGUST 25, 2023

In ML, there are a variety of algorithms that can help solve problems. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system. However, this does not mean you need to code the algorithms from scratch (roll your own). 12, 2014. [3]

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Viso.ai

DECEMBER 19, 2023

Today, the use of convolutional neural networks (CNN) is the state-of-the-art method for image classification. This means machine learning algorithms are used to analyze and cluster unlabeled datasets by discovering hidden patterns or data groups without the need for human intervention. How Does Image Classification Work?

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Marktechpost

JULY 18, 2023

First, let’s have a peek at the best object detection algorithms currently available. The HOG algorithm employs a gradient orientation process to pinpoint an image’s most crucial features. Fast R-CNN The Fast R-CNN technique, or Fast Region-Based Convolutional Network method, is a training algorithm for detecting objects.

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Viso.ai

JUNE 26, 2024

This article will discuss the following: Neuromorphic Engineering and its core principles History and Development Algorithms Used How Neuromorphic Algorithms differ from Traditional Algorithms Real-world examples Applications and Use Cases About Us: At Viso.ai, we power Viso Suite, the most complete end-to-end computer vision platform.

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Viso.ai

DECEMBER 10, 2023

An introduction The basic concepts and how it works Traditional and modern deep learning image recognition The best popular image recognition algorithms How to use Python for image recognition Examples and deep learning applications Popular image recognition software About: We provide the leading end-to-end computer vision platform Viso Suite.

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NVIDIA

AUGUST 29, 2024

Soon after those papers were published in 2017 and 2018, Kiela and his team of AI researchers at Facebook, where he worked at that time, realized LLMs would face profound data freshness issues. In addition to greater accuracy, its offering lowers latency thanks to fewer API calls between the RAG’s and LLM’s neural networks.

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Viso.ai

OCTOBER 10, 2024

We will elaborate on computer vision techniques like Convolutional Neural Networks (CNNs). It is not feasible to manually label enough satellite photos and train algorithms to comprehend visual data. 2023) utilized Satellite Image Time Series (SITS) with about 50 satellite datasets, gathered in the period 2017-2023.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

NYU Center for Data Science

AUGUST 24, 2023

Understanding the Math Behind Neural Nets These scientific discussions branch off in many directions, but one common goal within the MaD group is to develop a mathematical understanding of neural networks. “We The idea is to shed light on the “fundamental mathematical principles that explain [neural nets’] behavior.”

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Towards AI

AUGUST 8, 2024

These experts are the specialized neural networks. Then, there’s the gating network, like a smart manager who knows exactly which expert to call on based on the task at hand. Transformers architecture, introduced back in 2017, revolutionized AI, particularly in language models.

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AssemblyAI

MAY 3, 2023

With these fairly complex algorithms often being described as “giant black boxes” in news and media, a demand for clear and accessible resources is surging. Artificial neural networks consist of interconnected layers of nodes, or “neurons” which work together to process and learn from data.

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Unite.AI

JULY 23, 2024

At the heart of YouCam Makeup is its extensive hairstyle try-on tool, powered by state-of-the-art AI algorithms. Developed by FaceApp Technology Limited, this app has garnered immense popularity since its 2017 launch, amassing over 500 million downloads. The app's hairstyle and hair color changing feature is particularly noteworthy.

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Viso.ai

FEBRUARY 11, 2024

The Need for Image Training Datasets To train the image classification algorithms we need image datasets. These datasets contain multiple images similar to those the algorithm will run in real life. The labels provide the Knowledge the algorithm can learn from. Algorithms that won the ImageNet challenge by year – source.

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Viso.ai

JULY 9, 2024

Neural Networks For now, most attempts to develop ASI are still grounded in well-known models, such as neural networks , machine learning/deep learning , and computational neuroscience. Diagram that illustrates the reinforcement learning process through agent-environment interaction and the constituent ranking algorithm.

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Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

ML @ CMU

SEPTEMBER 13, 2024

2017 ] may look like tests for memorization and they are even intimately related to auditing machine unlearning [ Carlini et al., In this section, we formally define and introduce our MiniPrompt algorithm that we use to answer our central question. The secret sharer: Evaluating and testing unintended memorization in neural networks.

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AssemblyAI

MAY 23, 2023

With these complex algorithms often labeled as "giant black boxes" in media, there's a growing need for accurate and easy-to-understand resources, especially for Product Managers wondering how to incorporate AI into their product roadmap. Neural Networks and Transformers What determines a language model's effectiveness?

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Viso.ai

JULY 17, 2024

Background and History of Neural Style Transfer NST is an example of an image styling problem that has been in development for decades, with image analogies and texture synthesis algorithms paving foundational work for NST. Layer Reconstruction in VGG-19 network for style transfer. Here is the journey of NST. Gatys et al.

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Unite.AI

OCTOBER 27, 2023

For example, multimodal generative models of neural networks can produce such images, literary and scientific texts that it is not always possible to distinguish whether they are created by a human or an artificial intelligence system. Stiglitz, will lead to the transformation of civilization (Stiglitz, 2017).

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PyImageSearch

OCTOBER 30, 2023

Spotify’s Discover Weekly ( Figure 3 ) is an algorithm-generated playlist released every Monday to offer its listeners custom, curated music recommendations. to train their algorithm. Alternating Least Squares The matrices and are optimized using alternate least squares algorithm as follows: Step 1: Initialize and randomly.

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Mlearning.ai

FEBRUARY 10, 2023

Addressing bias and Variance Here is the solution to address bias and variance problems: If you have a high avoidable bias; then it is recommended to use a bigger model i.e. a neural network with more hidden layers and hidden units. A more giant network and big data will improve the performance significantly. References [1].Ng,

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Heartbeat

MARCH 14, 2023

By incorporating computer vision methods and algorithms into robots, they are able to view and understand their environment. Object recognition and tracking algorithms include the CamShift algorithm , Kalman filter , and Particle filter , among others.

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Computer Vision Robotics Deep Learning Convolutional Neural Networks 97

Viso.ai

JANUARY 16, 2024

Artificial Neural Networks (ANNs) are the cornerstone of modern artificial intelligence (AI). This diagram showcases how various layers interact in a neural network – source. Traditional software operates based on predefined, linear rules and algorithms explicitly programmed by humans. The algorithm creator?

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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. 1], (d) image by Shiwa ID on Unsplash. f, 0.4822f*255.f,

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Towards AI

JULY 20, 2023

That’s great news for researchers who often work on SLRs because the traditional process is mind-numbingly slow: An analysis from 2017 found that SLRs take, on average, 67 weeks to produce. As the capabilities of high-powered computers and ML algorithms have grown, so have opportunities to improve the SLR process. dollars apiece.

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Lexalytics

APRIL 5, 2021

This book effectively killed off interest in neural networks at that time, and Rosenblatt, who died shortly thereafter in a boating accident, was unable to defend his ideas. (I Around this time a new graduate student, Geoffrey Hinton, decided that he would study the now discredited field of neural networks.

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Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Viso.ai

JULY 9, 2024

Computer vision researchers introduced YOLO architecture (You Only Look Once) as an object-detection algorithm in 2015. It was a single-pass algorithm having only one neural network to predict bounding boxes and class probabilities using a full image as input. The model achieved 43.5 mAP at 65 FPS on the COCO dataset.

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Viso.ai

JUNE 12, 2024

GPT models are based on transformer-based deep learning neural network architecture. At first, recurrent ( RNN ) networks, in particular, LSTM, were mainstream in this area. But after the invention of the Transformer architecture in the summer of 2017 by OpenAI, GPT-2 gradually began to prevail in conversational tasks.

Large Language Models 52

Large Language Models ChatGPT Computer Vision Neural Network 52

Towards AI

APRIL 8, 2024

Word2Vec, a widely-adopted NLP algorithm has proven to be an efficient and valuable tool that is now applied across multiple domains, including recommendation systems. million unique users, capturing listens across 25 million unique songs gathered between 2017 and 2023.

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Heartbeat

DECEMBER 8, 2023

This includes cleaning and transforming data, performing calculations, or applying machine learning algorithms. is well known for his work on optical character recognition and computer vision using convolutional neural networks (CNN), and is a founding father of convolutional nets.

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Google Research AI blog

FEBRUARY 2, 2023

With the increasing sophistication of the algorithms and hardware in use today and with the scale at which they run, the complexity of the software necessary to carry out day-to-day tasks only increases. NaaS goes even further by searching for neural network architectures and hardware architectures together.

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deepsense.ai

APRIL 16, 2023

Pipeline Parallelism Since deep neural networks typically have multiple layers stacked on top of each other, the naive approach to model parallelism involves dividing a large model into smaller parts, with a few consecutive layers grouped together and assigned to a separate device, with the output of one stage serving as the input to the next stage.

Large Language Models 52

Large Language Models Neural Network Deep Learning Explainability 52

Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., Understanding the robustness of image segmentation algorithms to adversarial attacks is critical for ensuring their reliability and security in practical applications.

Computer Vision 52

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Viso.ai

OCTOBER 7, 2024

This is an iterative approach where the user interacts with a machine-learning algorithm such as a computer vision (CV) system and provides feedback on its outputs. This iterative approach involves user interaction with a machine-learning algorithm, such as a computer vision (CV) system, providing feedback on its outputs.

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