Applied Data Science

AUGUST 2, 2021

This post is a bitesize walk-through of the 2021 Executive Guide to Data Science and AI  — a white paper packed with up-to-date advice for any CIO or CDO looking to deliver real value through data. Machine learning The 6 key trends you need to know in 2021 ? Download the free, unabridged version here.

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Data Science Data Scientist Machine Learning Automation 52

Lexalytics

JULY 12, 2023

We’ve pioneered a number of industry firsts, including the first commercial sentiment analysis engine, the first Twitter/microblog-specific text analytics in 2010, the first semantic understanding based on Wikipedia in 2011, and the first unsupervised machine learning model for syntax analysis in 2014.

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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. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system.

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Towards AI

JULY 20, 2023

The Lookout — “All’s Well” | Homer NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER The NLP Cypher | 03.07.21 You can talk with AI with only one line of code… github.com AI Index 2021 The yearly and comprehensive report on AI is out. The Crow’s Nest Hey Welcome back! For NLP focused content, start on page 62.

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IBM Journey to AI blog

JULY 11, 2023

According to Statista , the artificial intelligence (AI) healthcare market, valued at $11 billion in 2021, is projected to be worth $187 billion in 2030. One use case example is out of the University of Hawaii, where a research team found that deploying deep learning AI technology can improve breast cancer risk prediction.

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Viso.ai

OCTOBER 9, 2024

With the rapid development of Convolutional Neural Networks (CNNs) , deep learning became the new method of choice for emotion analysis tasks. Unsurprisingly, modern deep learning methods outperform traditional computer vision methods. However, privacy concerns still arise when emotion analysis is used for user profiling.

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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. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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AssemblyAI

NOVEMBER 9, 2023

In Natural Language Processing (NLP), Text Summarization models automatically shorten documents, papers, podcasts, videos, and more into their most important soundbites. The models are powered by advanced Deep Learning and Machine Learning research. What is Text Summarization for NLP? 67:34: He said the U.S.

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Towards AI

JULY 20, 2023

Natural Language Processing Getting desirable data out of published reports and clinical trials and into systematic literature reviews (SLRs) — a process known as data extraction — is just one of a series of incredibly time-consuming, repetitive, and potentially error-prone steps involved in creating SLRs and meta-analyses.

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Data Extraction NLP Natural Language Processing Automation 75

Mlearning.ai

JUNE 14, 2023

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube YouTube Introduction to Natural Language Processing (NLP) NLP 2012 Dan Jurafsky and Chris Manning (1.1)

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Neural Network BERT Large Language Models Natural Language Processing 52

IBM Journey to AI blog

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. The term “foundation model” was coined by the Stanford Institute for Human-Centered Artificial Intelligence in 2021.

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AWS Machine Learning Blog

OCTOBER 5, 2023

He focuses on developing scalable machine learning algorithms. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering. an AI start-up, and worked as the CEO and Chief Scientist in 2019–2021.

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Machine Learning Big Data Deep Learning Natural Language Processing 124

NVIDIA Developer

MAY 20, 2021

Chung , posted May 21 2021 at 12:03AM Businesses worldwide are using artificial intelligence to solve their greatest challenges. Deep learning is a powerful AI approach that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation.

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Sebastian Ruder

NOVEMBER 14, 2022

Developing models that work for more languages is important in order to offset the existing language divide and to ensure that speakers of non-English languages are not left behind, among many other reasons. This post is partially based on a keynote I gave at the Deep Learning Indaba 2022. Label: FALSE (Liu et al.,

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

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. All pharma giants, including Bayer, AstraZeneca, Takeda, Sanofi, Merck, and Pfizer, have stepped up spending in the hope to create new-age AI solutions that will bring cost efficiency, speed, and precision to the process.

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Neural Network Deep Learning Artificial Intelligence Artificial Intelligence 139

Flipboard

JULY 10, 2023

Figure 4: Architecture of fully connected autoencoders (source: Amor, “Comprehensive introduction to Autoencoders,” ML Cheat Sheet , 2021 ). Figure 5: Architecture of Convolutional Autoencoder for Image Segmentation (source: Bandyopadhyay, “Autoencoders in Deep Learning: Tutorial & Use Cases [2023],” V7Labs , 2023 ).

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ODSC - Open Data Science

APRIL 3, 2023

Question Answering is the task in Natural Language Processing that involves answering questions posed in natural language. Her main research interests are in machine learning for large-scale language understanding and text semantics. Euro) in 2021. Don’t worry, you’re not alone! Iryna Gurevych.

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Neural Network Natural Language Processing NLP Computational Linguistics 117

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.

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Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

Heartbeat

JULY 6, 2023

The process of locating and identifying objects of interest in an image or video is part of the object detection method, a popular computer vision technique. Object detection is typically achieved through the use of deep learning models, particularly Convolutional Neural Networks (CNNs). What is the Swin Transformer?

Computer Vision 59

Computer Vision Convolutional Neural Networks Deep Learning Neural Network 59

Sebastian Ruder

AUGUST 23, 2021

Recent models "have outpaced the benchmarks to test for them" ( AI Index Report 2021 ), quickly reaching super-human performance on standard benchmarks such as SuperGLUE and SQuAD. Does this mean that we have solved natural language processing? Far from it. Header image: Performance on SQuAD 2.0

NLP 52

NLP Natural Language Processing ML Deep Learning 52

Mlearning.ai

APRIL 10, 2023

Supervised machine learning (such as SVM or GradientBoost) and deep learning models (such as CNN or RNN) can promise far superior performances when comparing them to clustering models however this can come at a greater cost with marginal rewards to the environment, end-user, and product owner of such technology. Wang and H.

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Algorithm Machine Learning Data Analysis Deep Learning 52

Topbots

APRIL 11, 2023

In the rapidly evolving field of artificial intelligence, natural language processing has become a focal point for researchers and developers alike. The Most Important Large Language Models (LLMs) in 2023 1. Its design allowed the model to consider the context from both the left and the right sides of each word.

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NVIDIA

NOVEMBER 16, 2023

billion in 2021 alone. The AI model trained on that data learned to understand the intent of incoming emails through natural language processing capabilities in NVIDIA Morpheus , a framework for AI-powered cybersecurity.

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Viso.ai

FEBRUARY 25, 2023

Transformer models have become the de-facto status quo in Natural Language Processing (NLP). For example, the popular ChatGPT AI chatbot is a transformer-based language model. They are based on the transformer architecture, which was originally proposed for natural language processing (NLP) in 2017.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Viso.ai

JUNE 12, 2024

Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. GPT models are based on transformer-based deep learning neural network architecture. About us : Viso.ai Get a demo here.

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Large Language Models ChatGPT Computer Vision Neural Network 52

Snorkel AI

MAY 4, 2023

Details at a glance: Date: June 7 – 8, 2023 Time: 8am – 2:30pm PT / each day Format: Virtual and free Register for free today Data-centric AI: vital now more than ever AI has experienced remarkable advancements in recent months, driven by innovations in machine learning, particularly deep learning techniques.

Computer Vision 52

Computer Vision Large Language Models AI AI 52

Snorkel AI

MAY 4, 2023

Details at a glance: Date: June 7 – 8, 2023 Time: 8am – 2:30pm PT / each day Format: Virtual and free Register for free today Data-centric AI: vital now more than ever AI has experienced remarkable advancements in recent months, driven by innovations in machine learning, particularly deep learning techniques.

Computer Vision 52

Computer Vision Large Language Models AI AI 52

NYU Center for Data Science

JULY 21, 2023

2021, is a nexus in another way, too. But they point out that the deeper reason for the field’s explosion is the deep learning paradigm we’ve been in for the past decade, which has allowed researchers from disparate specialties to talk to each other. Similar overhead was required to do research in natural language processing.

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AWS Machine Learning Blog

AUGUST 14, 2023

In this post and accompanying notebook, we demonstrate how to deploy the BloomZ 176B foundation model using the SageMaker Python simplified SDK in Amazon SageMaker JumpStart as an endpoint and use it for various natural language processing (NLP) tasks. He focuses on developing scalable machine learning algorithms.

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NLP Robotics Prompt Engineer Prompt Engineering 84

Bugra Akyildiz

JANUARY 20, 2024

Hierarchical reasoning model: AMIE employs a hierarchical reasoning model encompassing medical knowledge bases, probabilistic reasoning modules, and natural language processing (NLP) components. Natural language processing: AMIE utilizes NLP techniques for understanding and responding to clinician/patient queries.

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Natural Language Processing NLP Data Science Deep Learning 52

Mlearning.ai

MARCH 9, 2023

Recent studies have demonstrated that deep learning-based image segmentation algorithms are vulnerable to adversarial attacks, where carefully crafted perturbations to the input image can cause significant misclassifications (Xie et al., Towards deep learning models resistant to adversarial attacks. 2018; Sitawarin et al.,

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Computer Vision Deep Learning Machine Learning Algorithm 52

Heartbeat

JANUARY 18, 2024

Understanding Llama v2 Llama 2, a natural language processing library from Meta, consists of pre-trained and fine-tuned large language models (LLMs) whose scale ranges from 7 billion to 70 billion parameters. which is based on data up to 2021, Llama2 is trained on data up to December 2022. or even GPT 4?

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John Snow Labs

JUNE 5, 2023

Sentence detection is an essential component in many natural language processing (NLP) tasks, as it enables the analysis of text at a more granular level by breaking it down into individual sentences. Sentence Detection in Spark NLP is the process of automatically identifying the boundaries of sentences in a given text.

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NLP Natural Language Processing Deep Learning Algorithm 52

Pickl AI

FEBRUARY 2, 2023

The global AI in retail is expected to swell from under $5 billion in 2021 to more than $31 billion by 2028. The company has also developed an AI copywriting product that leverages deep learning models and natural language processing.

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Artificial Intelligence Artificial Intelligence Data Science AI 52

Heartbeat

AUGUST 2, 2023

Introduction to LLMs LLM in the sphere of AI Large language models (often abbreviated as LLMs) refer to a type of artificial intelligence (AI) model typically based on deep learning architectures known as transformers. The positional encoding allows the model to understand the sequential nature of language.

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Viso.ai

MAY 1, 2024

Deep learning and Convolutional Neural Networks (CNNs) have enabled speech understanding and computer vision on our phones, cars, and homes. Natural Language Processing (NLP) and knowledge representation and reasoning have empowered the machines to perform meaningful web searches. Brooks et al.

Robotics 52

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Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Deep learning models with multilayer processing architecture are now outperforming shallow or standard classification models in terms of performance [5]. Foundations of Statistical Natural Language Processing [M].

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