ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. In a change from last year, there’s also a higher demand for those with data analysis skills as well.

Deep Learning 111

Deep Learning Deep Learning Data Science Natural Language Processing 111

PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

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.

Deep Learning 126

Deep Learning Deep Learning AI AI 126

AWS Machine Learning Blog

FEBRUARY 29, 2024

Large-scale deep learning has recently produced revolutionary advances in a vast array of fields. is a startup dedicated to the mission of democratizing artificial intelligence technologies through algorithmic and software innovations that fundamentally change the economics of deep learning. Founded in 2021, ThirdAI Corp.

AWS 134

AWS Deep Learning Deep Learning ML 134

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.

AWS 126

AWS Machine Learning Machine Learning Deep Learning 126

Flipboard

JULY 10, 2023

Figure 5: Architecture of Convolutional Autoencoder for Image Segmentation (source: Bandyopadhyay, “Autoencoders in Deep Learning: Tutorial & Use Cases [2023],” V7Labs , 2023 ). time series or natural language processing tasks). This architecture is well-suited for handling sequential data (e.g.,

Deep Learning 132

Deep Learning Deep Learning Machine Learning Machine Learning 132

Towards AI

JULY 23, 2023

In the first part of the series, we talked about how Transformer ended the sequence-to-sequence modeling era of Natural Language Processing and understanding. Generating Wikipedia By Summarizing Long Sequences This work was published by Peter J Liu at Google in 2019.

Natural Language Processing 98

Natural Language Processing Supervised Learning Deep Learning Deep Learning 98

AWS Machine Learning Blog

APRIL 19, 2023

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. With the DJL, integrating this deep learning is simple. The DJL was created at Amazon and open-sourced in 2019. The architecture of DJL is engine agnostic.

ML 98

ML ML Deep Learning Deep Learning 98

Towards AI

FEBRUARY 10, 2023

Building natural language processing and computer vision models that run on the computational infrastructures of Amazon Web Services or Microsoft’s Azure is energy-intensive. The Myth of Clean Tech: Cloud Data Centers The data center has been a critical component of improvements in computing.

AI 98

AI AI Natural Language Processing Artificial Intelligence 98

Hacker News

MARCH 25, 2022

“Transformers made self-supervised learning possible, and AI jumped to warp speed,” said NVIDIA founder and CEO Jensen Huang in his keynote address this week at GTC. Transformers are in many cases replacing convolutional and recurrent neural networks (CNNs and RNNs), the most popular types of deep learning models just five years ago.

Machine Learning 182

Machine Learning Machine Learning Database AI 182

Smart Data Collective

MARCH 26, 2021

Due to its constant learning and evolution, the algorithms are able to adapt based on success and failure. Machine learning mimics the human brain. It entails deep learning from its neural networks, natural language processing (NLP), and constant changes based on incoming information.

Machine Learning 143

Machine Learning Machine Learning ML ML 143

Dataconomy

OCTOBER 22, 2024

In 2019, 65% of graduating North American PhDs in AI opted for industry roles , a significant jump from 44.4% These datasets provide the necessary scale for training advanced machine learning models, which would be difficult for most academic labs to collect independently.

AI 113

AI AI Natural Language Processing Machine Learning 113

Smart Data Collective

FEBRUARY 24, 2021

Machine Learning to Write your College Essays. Earlier in 2019, the AI development company OpenAI developed a text-writing algorithm named GPT-2 that could use machine learning to generate content. In order to achieve this, Grammarly’s technology combines machine learning with natural language processing approaches.

Machine Learning 103

Machine Learning Machine Learning Natural Language Processing AI 103

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)

Natural Language Processing 52

Natural Language Processing ML ML Support Vector Machines 52

Mlearning.ai

FEBRUARY 19, 2023

You don’t need to have a PhD to understand the billion parameter language model GPT is a general-purpose natural language processing model that revolutionized the landscape of AI. GPT-3 is a autoregressive language model created by OpenAI, released in 2020 . What is GPT-3?

Natural Language Processing 52

Natural Language Processing Deep Learning Deep Learning Artificial Intelligence 52

Applied Data Science

DECEMBER 23, 2022

In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. It is not surprising that it has become a major application area for deep learning.

AI 130

AI AI Data Science Deep Learning 130

Heartbeat

JANUARY 23, 2023

Image from Hugging Face Hub Introduction Most natural language processing models are built to address a particular problem, such as responding to inquiries regarding a specific area. This restricts the applicability of models for understanding human language. Alex Warstadt et al. print("1-",qqp["train"].homepage)

Natural Language Processing 52

Natural Language Processing Deep Learning Deep Learning ML 52

Heartbeat

JUNE 6, 2023

In recent years, researchers have also explored using GCNs for natural language processing (NLP) tasks, such as text classification , sentiment analysis , and entity recognition. Once the GCN is trained, it is easier to process new graphs and make predictions about them. Richong, Z., Yongyi, M., & Xudong L.

Natural Language Processing 59

Natural Language Processing Deep Learning Deep Learning Machine Learning 59

AWS Machine Learning Blog

APRIL 29, 2024

Historically, natural language processing (NLP) would be a primary research and development expense. In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows.

AWS 125

AWS ML ML Python 125

How to Learn Machine Learning

JULY 20, 2024

In this article you will learn about 7 of the top Generative AI Trends to watch out for in this year, so please please sit back relax, enjoy, and learn! It falls under machine learning and uses deep learning algorithms and programs to create music, art, and other creative content based on the user’s input.

AI 65

AI AI Machine Learning Machine Learning 65

Pickl AI

JANUARY 3, 2024

Geographic Variations: The average salary of a Machine Learning professional in India is ₹12,95,145 per annum. Career Advancement: Professionals can enhance earning potential by acquiring in-demand skills like Natural Language Processing, Deep Learning, and relevant certifications aligned with industry needs.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing Deep Learning 52

AWS Machine Learning Blog

JUNE 13, 2023

The first generation of AWS Inferentia, a purpose-built accelerator launched in 2019, is optimized to accelerate deep learning inference. Conclusion AWS Inferentia2 is a powerful technology designed for improving performance and reducing costs of deep learning model inference.

AWS 98

AWS ML ML Deep Learning 98

Towards AI

JULY 21, 2023

The Ninth Wave (1850) Ivan Aivazovsky NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 09.13.20 It leverages an interface across tasks that are grounded on a single knowledge source: the 2019/08/01 Wikipedia snapshot containing 5.9M Aere Perrenius Welcome back. Hope you enjoyed your week!

Natural Language Processing 98

Natural Language Processing Machine Learning Machine Learning AI 98

Heartbeat

AUGUST 23, 2023

But what if there was a technique to quickly and accurately solve this language puzzle? Enter Natural Language Processing (NLP) and its transformational power. But what if there was a way to unravel this language puzzle swiftly and accurately?

Natural Language Processing 52

Natural Language Processing Algorithm Artificial Intelligence Artificial Intelligence 52

DrivenData Labs

DECEMBER 10, 2023

degree in AI and ML specialization from Gujarat University, earned in 2019. He also boasts several years of experience with Natural Language Processing (NLP). Itay possesses experience in machine learning, deep learning, and full stack development. He holds an M.S.

AI 147

AI AI Natural Language Processing Artificial Intelligence 147

Heartbeat

OCTOBER 10, 2023

One of the most popular techniques for speech recognition is natural language processing (NLP), which entails training machine learning models on enormous amounts of text data to understand linguistic patterns and structures. It was developed by Facebook AI Research and released in 2019.

Machine Learning 52

Machine Learning Machine Learning Deep Learning 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., 2019) or by using input pre-processing techniques to remove adversarial perturbations (Xie et al.,

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Heartbeat

MARCH 15, 2023

Photo by Fatos Bytyqi on Unsplash Introduction Did you know that in the past, computers struggled to understand human languages? But now, a computer can be taught to comprehend and process human language through Natural Language Processing (NLP), which was implemented, to make computers capable of understanding spoken and written language.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Heartbeat

MARCH 22, 2023

RoBERTa: A Modified BERT Model for NLP — by Khushboo Kumari An open-source machine learning model called BERT was developed by Google in 2018 for NLP, but this model had some limitations, and due to this, a modified BERT model called RoBERTa (Robustly Optimized BERT Pre-Training Approach) was developed by the team at Facebook in the year 2019.

Natural Language Processing 40

Natural Language Processing EDA Machine Learning Machine Learning 40

The MLOps Blog

APRIL 5, 2023

For example, Modularizing a natural language processing (NLP) model for sentiment analysis can include separating the word embedding layer and the RNN layer into separate modules, which can be packaged and reused in other NLP models to manage code and reduce duplication and computational resources required to run the model.

ML 69

ML ML Machine Learning Machine Learning 69

Explosion

NOVEMBER 21, 2019

Try the new interactive demo to explore similarities and compare them between 2015 and 2019 sense2vec (Trask et. al, 2015) is a twist on the word2vec family of algorithms that lets you learn more interesting word vectors. Named entity annotations and noun phrases can also help, by letting you learn vectors for multi-word expressions.

Natural Language Processing 52

Natural Language Processing Data Scientist Machine Learning Machine Learning 52

ML Review

MAY 3, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part One) This is the first instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Thanks for reading!

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Machine Learning 52

Dataconomy

MARCH 15, 2023

Visual ChatGPT brings AI image generation to the popular chatbot Back to the present: GPT-4 is released The much-anticipated release of GPT-4 is now available to some Plus subscribers, featuring a new multimodal language model that accepts text, speech, images, and video as inputs and provides text-based answers.

AI 70

AI AI Natural Language Processing Artificial Intelligence 70

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Thirdly, the presence of GPUs enabled the labeled data to be processed. Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning. FP64 is used in HPC fields, such as the natural sciences and financial modeling, resulting in minimal rounding errors.

AWS 113

AWS ML ML Clustering 113

Heartbeat

JANUARY 29, 2024

Imagine an AI system that becomes proficient in many tasks through extensive training on each specific problem and a higher-order learning process that distills valuable insights from previous learning endeavors. Reptile is a meta-learning algorithm that falls under model-agnostic meta-learning approaches.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing Algorithm 52

Heartbeat

JUNE 28, 2023

In this article, we will explore about ALBERT ( A lite weighted version of BERT machine learning model) What is ALBERT? ALBERT (A Lite BERT) is a language model developed by Google Research in 2019. In this article, you can learn how distillation can be applied to ALBERT to reduce its size and improve its efficiency.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Snorkel AI

MAY 24, 2023

From generative modeling to automated product tagging, cloud computing, predictive analytics, and deep learning, the speakers present a diverse range of expertise. He leads corporate strategy for machine learning, natural language processing, information retrieval, and alternative data.

Machine Learning 52

Machine Learning Machine Learning Computer Science Computer Science 52