Towards AI

AUGUST 25, 2023

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. In ML, there are a variety of algorithms that can help solve problems. Any competent software engineer can implement any algorithm. 12, 2014. [3]

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DataSeries

AUGUST 15, 2024

Deep learning has a spectrum of architectures capable of constructing solutions across various domains. Explore the most popular types of deep learning architecture. Deep learning algorithms span a diverse array of architectures, each capable of crafting solutions for a wide range of problem domains.

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Applied Data Science

JANUARY 4, 2022

At the very least, we hope that by reading this list you can cross-out “Learning about the state of AI in 2021” from your resolution list ?. ? Transformers taking the AI world by storm The family of artificial neural networks (ANNs) saw a new member being born in 2017, the Transformer. What happens when you combine the two?

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AssemblyAI

MARCH 21, 2023

Top 50 keywords in submitted research papers at ICLR 2022 ( source ) A recent bibliometric study systematically analysed this research trend, revealing an exponential growth of published research involving GNNs, with a striking +447% average annual increase in the period 2017-2019.

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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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Dataconomy

FEBRUARY 6, 2024

This popularity is primarily due to the spread of big data and advancements in algorithms. Going back from the times when AI was merely associated with futuristic visions to today’s reality, where ML algorithms seamlessly navigate our daily lives. These technologies have undergone a profound evolution. billion by 2032.

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AWS Machine Learning Blog

MAY 16, 2024

Therefore, we decided to introduce a deep learning-based recommendation algorithm that can identify not only linear relationships in the data, but also more complex relationships. Recommendation model using NCF NCF is an algorithm based on a paper presented at the International World Wide Web Conference in 2017.

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Defined.ai blog

JANUARY 29, 2023

Generative Adversarial Networks (GANs) are a type of deep learning algorithm that’s been gaining popularity due to their ability to generate high-quality, realistic images and other types of data. As such, Generative Adversarial Networks are invaluable deep learning algorithms with almost endless beneficial potential.

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Dataconomy

DECEMBER 2, 2024

Emerging from TU Darmstadt’s award-winning “Team Hector,” the company gained global recognition by winning the 2017 ARGOS Challenge for developing the first robot capable of complex inspections on oil and gas platforms.

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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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Smart Data Collective

FEBRUARY 24, 2021

You might have received a lengthy email from your coworker, and you could simply press on the ‘Got it’ response suggested by Google’s AI algorithm to compose your reply. Machine Learning to Write your College Essays. Let us take a look at a few cases that will offer us more insight.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning. In 2017, the landmark paper “ Attention is all you need ” was published, which laid out a new deep learning architecture based on the transformer.

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Dataconomy

MAY 8, 2023

AI drawing generators use machine learning algorithms to produce artwork What is AI drawing? You might think of AI drawing as a generative art where the artist combines data and algorithms to create something completely new. They use deep learning models to learn from large sets of images and make new ones that meet the prompts.

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DrivenData Labs

JULY 19, 2023

Over the past few years, our team has run over 20 different machine learning competitions in the domain of climate change and AI, with over a million dollars awarded to developers of the top-performing approaches. From these, we've identified five distinct areas where AI is having an impact on climate action. ?

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PyImageSearch

JULY 3, 2023

Figure 1: Netflix Recommendation System (source: “Netflix Film Recommendation Algorithm,” Pinterest ). Netflix recommendations are not just one algorithm but a collection of various state-of-the-art algorithms that serve different purposes to create the complete Netflix experience.

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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.

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Pickl AI

APRIL 8, 2024

This blog explores 13 major AI blunders, highlighting issues like algorithmic bias, lack of transparency, and job displacement. From the moment we wake up to the personalized recommendations on our phones to the algorithms powering facial recognition software, AI is constantly shaping our world.

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Mlearning.ai

FEBRUARY 10, 2023

For example, if you are using regularization such as L2 regularization or dropout with your deep learning model that performs well on your hold-out-cross-validation set, then increasing the model size won’t hurt performance, it will stay the same or improve. In the big data and deep learning era, now you have much more flexibility.

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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. Kurakin et al, ICLR 2017. Source: Robust Physical-World Attacks on Deep Learning Visual Classification. Kurakin et al, ICLR 2017. Sharif et al. Eykholt et al.

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Mlearning.ai

APRIL 10, 2023

3 feature visual representation of a K-means Algorithm. Source: Marubon-DS Unsupervised Learning In the data science context, clustering is an unsupervised machine learning technique, this means that it does not require predefined labeled inputs or outcomes to learn from.

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DagsHub

FEBRUARY 8, 2024

The advancements in deep learning have resulted in exceptional precision rates for object detection. 2) Deep learning algorithms with two stages, including examples such as various R-CNN models faster object separation from the background with faster speeds and higher accuracy. Sercan Çayır et al.

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Dataconomy

MARCH 7, 2023

Its replies are a hybrid of pre-programmed scripts and machine-learning algorithms. Later, they employ cutting-edge AI instruments to learn the user’s goals. Luka, an AI startup founded in 2017, created it to communicate with a person who passed away. Modern AI chatbots employ NLU to grasp what the user tries to do.

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Mlearning.ai

JULY 31, 2023

Things become more complex when we apply this information to Deep Learning (DL) models, where each data type presents unique challenges for capturing its inherent characteristics. 2017) paper, vector embeddings have become a standard for training text-based DL models. Likewise, sound and text have no meaning to a computer.

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AWS Machine Learning Blog

AUGUST 16, 2023

Travelers collaborated with the Amazon Machine Learning Solutions Lab (now known as the Generative AI Innovation Center ) to develop this framework to support and enhance aerial imagery model use cases. The images document the land cover, or physical surface features, of ten European countries between June 2017 and May 2018.

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Hacker News

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. This process of adapting pre-trained models to new tasks or domains is an example of Transfer Learning , a fundamental concept in modern deep learning.

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Mlearning.ai

MAY 16, 2023

. * @return the predicted class */ std::string Inference(cv::Mat& src, AAssetManager* mgr); #endif //IMAGECLASSIFICATION_INFERENCE_H /** * inference.cpp */ #include <algorithm> #include <vector> #include <string> #include <opencv2/imgproc.hpp> #include "net.h" " #include "inference.h"

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Pickl AI

FEBRUARY 14, 2023

Significantly, by leveraging technologies like deep learning and proprietary algorithms for analytics, Artivatic.ai Arya.ai One of the growing AI companies in India, Arya.ai, deploys Deep Learning solutions for the BFSI sector. Artivatic.ai Artivatic.ai Accordingly, Beatoven.ai Bert Labs Pvt.

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Google Research AI blog

FEBRUARY 2, 2023

Great machine learning (ML) research requires great systems. 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. You can find other posts in the series here.) Mechanization.

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AssemblyAI

SEPTEMBER 4, 2023

” In fact, when our company was accepted into Y Combinator back in 2017, one of the first questions the YC partners asked us was “What’s your WER?” In the field of Automatic Speech Recognition, the Word Error Rate has become the de facto standard for measuring how accurate a speech recognition model is.

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ML Review

JUNE 4, 2018

2017)[ 51 ] Introduction to Image Captioning Suppose that we asked you to caption an image; that is to describe the image using a sentence. However, in 2014 a number of high-profile AI labs began to release new approaches leveraging deep learning to improve performance. Source: Lu et al. 2016)[ 91 ] You et al.

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Mlearning.ai

MAY 8, 2023

A comprehensive step-by-step guide with data analysis, deep learning, and regularization techniques Introduction In this article, we will use different deep-learning TensorFlow neural networks to evaluate their performances in detecting whether cell nuclei mass from breast imaging is malignant or benign.

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Heartbeat

OCTOBER 9, 2023

These ground-breaking areas redefine how we connect with and learn from our collective past. Computer vision algorithms can reconstruct a highly detailed 3D model by photographing objects from different perspectives. But computer vision algorithms can assist us in digitally scanning and preserving these priceless manuscripts.

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Mlearning.ai

MAY 23, 2023

With the advancement of technology, machine learning, and computer vision techniques can be used to develop automated solutions for leaf disease detection. In this article, we will discuss the development of a Leaf Disease Detection Flask App that uses a deep learning model to automatically detect the presence of leaf diseases.

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Heartbeat

DECEMBER 8, 2023

This includes cleaning and transforming data, performing calculations, or applying machine learning algorithms. LeCun received the 2018 Turing Award (often referred to as the "Nobel Prize of Computing"), together with Yoshua Bengio and Geoffrey Hinton, for their work on deep learning. Meta's chief A.I.

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Mlearning.ai

MAY 21, 2023

If you are interested in exploring machine learning and want to dive into practical implementation, working on machine learning projects with source code is an excellent way to start. These projects also enable you to grasp the practical aspects of solving real-world problems using machine-learning techniques.

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Mlearning.ai

JUNE 7, 2023

This is going to be an interesting blog, so without any further due, let’s start… Machine learning has revolutionized various industries, from healthcare to finance and everything in between. However, building a machine learning model involves more than just training algorithms. We have the IPL data from 2008 to 2017.

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Heartbeat

JULY 20, 2023

However, the representation and processing of these unstructured, disordered, redundant, and unevenly distributed 3D data remain a significant challenge for segmentation algorithms. When evaluated on the MS COCO dataset test-dev 2017, YOLOv8x attained an impressive average precision (AP) of 53.9%

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