Applied Data Science

JANUARY 4, 2022

Hiding your 2021 resolution list under a glass of champagne? To write this post we shook the internet upside down for industry news and research breakthroughs and settled on the following 5 themes, to wrap up 2021 in a neat bow: ? Easy-going and widely used, there are cases when these networks lose to their more focused cousins.

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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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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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Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP).   2021 saw the continuation of the development of ever larger pre-trained models. 2021 saw the development of alternative model architectures that are viable alternatives to the transformer. style loss.

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Viso.ai

MAY 20, 2023

The YOLOv7 algorithm is making big waves in the computer vision and machine learning communities. In this article, we will provide the basics of how YOLOv7 works and what makes it the best object detector algorithm available today. About us: Viso.ai provides the only end-to-end computer vision application platform, Viso Suite.

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IBM Journey to AI blog

MAY 6, 2024

The rise in the deployment of electronic patient-reported outcomes (ePROs), electronic clinical outcome assessments (eCOAs), and electronic informed consent (eConsent) from 2020 to 2021, primarily driven by contract research organizations underscores this shift.

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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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Heartbeat

NOVEMBER 14, 2023

Integrating XGboost with Convolutional Neural Networks Photo by Alexander Grey on Unsplash XGBoost is a powerful library that performs gradient boosting. One robust use case for XGBoost is integrating it with neural networks to perform a given task. It was envisioned by Thongsuwan et al.,

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Dlabs.ai

AUGUST 31, 2021

And you can expect them to cover topics as far-flung as business intelligence, machine learning, deep learning, AI algorithms, virtual assistants, and chatbots. Big Data Conference Europe 2021 Date: September 28-30th Place: Online Ticket: 238 – 544 EUR The Big Data Conference covers more than its name suggests.

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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.

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The Stanford AI Lab Blog

DECEMBER 6, 2021

The thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021 is being hosted virtually from Dec 6th - 14th. Some of the members in our SAIL community also serve as co-organizers of several exciting workshops that will take place on Dec 13-14, so we hope you will check them out! Smith, Scott W. Low, Caitlin S.

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AWS Machine Learning Blog

MAY 15, 2023

Getir used Amazon Forecast , a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts, to increase revenue by four percent and reduce waste cost by 50 percent. Deep/neural network algorithms also perform very well on sparse data set and in cold-start (new item introduction) scenarios.

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Flipboard

APRIL 4, 2023

The crux of the clash was whether Google’s AI solution to one of chip design’s thornier problems was really better than humans or state-of-the-art algorithms. In Circuit Training and Morpheus, a separate algorithm fills in the gaps with the smaller parts, called standard cells. Wash, rinse, repeat. Kahng was reviewer #3.)

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Mlearning.ai

NOVEMBER 29, 2023

All the previously, recently, and currently collected data is used as input for time series forecasting where future trends, seasonal changes, irregularities, and such are elaborated based on complex math-driven algorithms. Neural networks are great in this application as they can learn the temporal dependence from the given data.

Machine Learning 52

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deepsense.ai

FEBRUARY 28, 2024

LLMs are machine learning models based on deep neural networks, capable of generating text by autoregressively predicting the next word (or the next token , to be more precise). It is worth mentioning one more data type, designed specifically with deep neural networks in mind – bfloat16 (brain floating point).

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Heartbeat

OCTOBER 18, 2023

By leveraging the power of neural networks, deep learning techniques breathe new life into recommendation algorithms, empowering them to handle complex data and surpass the limitations of their predecessors. Netflix’s movies and TV shows are recommended based on user ratings, viewing history, and platform interactions.

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Mlearning.ai

JUNE 14, 2023

YouTube Introduction to Sequence Learning and Attention Mechanisms Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 8 — Translation, Seq2Seq, Attention — YouTube Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 7 — Translation, Seq2Seq, Attention — YouTube 2. Transformer Neural Networks — EXPLAINED!

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Neural Network Large Language Models BERT Natural Language Processing 52

Flipboard

JUNE 20, 2023

Rather than humans programming computers with specific step-by-step instructions on how to complete a task, in machine learning a human provides the AI with data and asks it to achieve a certain outcome via an algorithm. Neural networks Neural networks are found in the human brain.

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Becoming Human

MARCH 16, 2023

Overhyped or not, investments in AI drug discovery jumped from $450 million in 2014 to a whopping $58 billion in 2021. AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. AI drug discovery is exploding.

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Unite.AI

MAY 10, 2024

Realizing that many of the tedious development processes in Mellanox could be automated by machine-learning algorithms, I changed my majors to optimization and machine learning and completed an MSc in the space. At Visualead, we’d been running algorithms on mobile devices since 2012, including models.

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AWS Machine Learning Blog

DECEMBER 7, 2023

Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Calculating courier requirements The first step is to estimate hourly demand for each warehouse, as explained in the Algorithm selection section.

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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. years, a 0.16% increase from 2021.

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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.

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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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Bugra Akyildiz

DECEMBER 18, 2022

Brown researchers compared human visual recognition systems and Deep Neural Networks for what they believe where the important features of images are. Neural Tangents is a high-level neural network API for specifying complex, hierarchical, neural networks of both finite and infinite width.

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deepsense.ai

FEBRUARY 28, 2024

LLMs are machine learning models based on deep neural networks, capable of generating text by autoregressively predicting the next word (or the next token , to be more precise). It is worth mentioning one more data type, designed specifically with deep neural networks in mind – bfloat16 (brain floating point).

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Pickl AI

JANUARY 29, 2024

Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. Key takeaways Data Science lays the groundwork for Machine Learning, providing curated datasets for ML algorithms to learn and make predictions. Emphasises programming skills, understanding of algorithms, and expertise in Data Analysis.

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IBM Journey to AI blog

AUGUST 1, 2023

Foundation models: The driving force behind generative AI Also known as a transformer, a foundation model is an AI algorithm trained on vast amounts of broad data. The term “foundation model” was coined by the Stanford Institute for Human-Centered Artificial Intelligence in 2021.

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TheSequence

JUNE 2, 2023

For instance, GPT-4 was trained on data dating back to Sep 2021. To mitigate disinformation from this ‘hallucinated’ response, OpenAI recently added the ‘As of my knowledge cutoff in September 2021,’ prefix ahead of such responses. What are LLM hallucinations?

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Pickl AI

SEPTEMBER 3, 2023

Key Takeaways: As of 2021, the market size of Machine Learning was USD 25.58 The specific techniques and algorithms used can vary based on the nature of the data and the problem at hand. Density-Based Spatial Clustering of Applications with Noise (DBSCAN): DBSCAN is a density-based clustering algorithm. CAGR during 2022-2030.

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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.

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Google Research AI blog

MARCH 30, 2023

Despite the fundamental importance of data to ML, it’s only now beginning to receive the same level of attention that models and learning algorithms have been enjoying for the past decade. Before modern deep neural networks (DNNs), there were no ML models sufficient to match human behavior for many simple tasks.

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Towards AI

JULY 20, 2023

As the capabilities of high-powered computers and ML algorithms have grown, so have opportunities to improve the SLR process. New research has also begun looking at deep learning algorithms for automatic systematic reviews, According to van Dinter et al.

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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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AWS Machine Learning Blog

OCTOBER 30, 2023

For the full list of model IDs, refer to Built-in Algorithms with pre-trained Model Table. To see the whole list of models available with SageMaker JumpStart, refer to Built-in Algorithms with pre-trained Model Table. In 2021, he presented a paper on adversarial neural networks at the ICLR conference.

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ODSC - Open Data Science

OCTOBER 18, 2023

A 2021 VentureBeat analysis suggests that 87% of AI models never make it to a production environment and an MIT Sloan Management Review article found that 70% of companies reported minimal impact from AI projects. It continues with the selection of a clustering algorithm and the fine-tuning of a model to create clusters.

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Marktechpost

JULY 24, 2023

Up-to-date machine learning-based data-driven techniques directly handle downstream forecasting or projection tasks by training a data-driven functional mapping in deep neural networks. These networks lack numerical model generality since they are trained on limited and consistent climate data for discrete spatiotemporal tasks.

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