Data Science Dojo

FEBRUARY 8, 2024

In the ever-evolving landscape of natural language processing (NLP), embedding techniques have played a pivotal role in enhancing the capabilities of language models. Fast forward to 2016, Facebook’s FastText introduced a significant shift by considering sub-word information.

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Data Science Dojo

DECEMBER 8, 2023

For instance, in natural language processing, a model trained on various languages might be tasked with translating a language it has never seen before. This comprehensive evaluation sheds light on the landscape of zero-shot learning methodologies, exploring the strengths and challenges across various approaches.

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Towards AI

APRIL 12, 2023

All of these companies were founded between 2013–2016 in various parts of the world. Soon to be followed by large general language models like BERT (Bidirectional Encoder Representations from Transformers).

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Her research interests lie in Natural Language Processing, AI4Code and generative AI. He joined Amazon in 2016 as an Applied Scientist within SCOT organization and then later AWS AI Labs in 2018 working on Amazon Kendra. His research interests lie in the area of AI4Code and Natural Language Processing.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Context (Snippet from PDF file) Question Answer THIS STRATEGIC ALLIANCE AGREEMENT (Agreement) is made and entered into as of November 6, 2016 (the Effective Date) by and between Dialog Semiconductor (UK) Ltd., His area of research is all things natural language (like NLP, NLU, and NLG).

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Dataconomy

AUGUST 31, 2023

The company understood the potential of AI and introduced its tool back in 2016, Salesforce Einstein. In September 2016, Salesforce rolled out Einstein to perform the following activities: automate tasks; provide customer insights; proactively suggest actions; visualize conversation information; compile relevant and converting emails, etc.

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Dataconomy

APRIL 18, 2023

The basics of artificial intelligence include understanding the various subfields of AI, such as machine learning, natural language processing, computer vision, and robotics. Deep learning has been used in a wide range of applications, such as image and speech recognition, natural language processing, and autonomous vehicles.

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Explosion

OCTOBER 22, 2016

This is a guest post by Wah Loon Keng , the author of spacy-nlp , a client that exposes spaCy ’s NLP text parsing to Node.js (and other languages) via Socket.IO. Natural Language Processing and other AI technologies promise to let us build applications that offer smarter, more context-aware user experiences. CLI: 2.4.0,

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Explosion

NOVEMBER 9, 2016

Over the last six months, a powerful new neural network playbook has come together for Natural Language Processing. A four-step strategy for deep learning with text Embedded word representations, also known as “word vectors”, are now one of the most widely used natural language processing technologies.

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Pickl AI

JULY 24, 2024

” During this time, researchers made remarkable strides in natural language processing, robotics, and expert systems. Notable achievements included the development of ELIZA, an early natural language processing program created by Joseph Weizenbaum, which simulated human conversation.

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Snorkel AI

MARCH 1, 2023

This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Devlin et al.

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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?

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Dataconomy

OCTOBER 27, 2023

2 uses natural language processing to generate imagery based on your text prompts. It’s used that money to create an AI-powered scheduling tool that can optimize the schedules of you and your teammates. 2 – Best AI image generator A product of the OpenAI team – the group behind ChatGPT – DALL.E

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AWS Machine Learning Blog

MARCH 31, 2023

He has been with the Transportation Cabinet since 2016 working in various IT roles. The contact center is powered by Amazon Connect, and Max, the virtual agent, is powered by Amazon Lex and the AWS QnABot solution. Amazon Connect directs some incoming calls to the virtual agent (Max) by identifying the caller number.

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Dataconomy

JUNE 15, 2023

In 2016, Google’s AI AlphaGo defeated Lee Sedol and Fan Hui, the European and world champions in the game of Go. They use natural language processing (NLP) techniques to understand and interpret user inputs, respond with relevant information, and carry out tasks or provide assistance.

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Dataconomy

DECEMBER 29, 2023

Launched in 2016 as an Instagram profile, Lil Miquela has since expanded her presence to TikTok and has amassed millions of followers on both platforms. Natural language processing (NLP) and machine learning algorithms can enhance the influencer’s ability to engage with users.

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DagsHub

JULY 25, 2024

Further Reading TensorFlow Documentation TensorFlow Tutorials PyTorch PyTorch, developed by Facebook's AI Research Lab (FAIR) , was released in 2016. Libraries and Extensions: Includes torchvision for image processing, touchaudio for audio processing, and torchtext for NLP.

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Smart Data Collective

DECEMBER 19, 2019

In 2016, A Facebook bot tricked more than 10,000 Facebook users. Augmenting learning along with analysis through natural language processing. Also, whenever we visit any website, chatbots reply to our common queries. But, their capability is beyond just answering our questions, or helping us in an online store.

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ML Review

JUNE 4, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part Two) This is the second instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). 2016)[ 91 ] You et al. Source : You et al.

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AWS Machine Learning Blog

APRIL 18, 2023

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

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Heartbeat

FEBRUARY 2, 2024

Visual Question Answering (VQA) stands at the intersection of computer vision and natural language processing, posing a unique and complex challenge for artificial intelligence. is a significant benchmark dataset in computer vision and natural language processing. or Visual Question Answering version 2.0,

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Mlearning.ai

APRIL 10, 2023

2016) Data Management : By allowing clustering to occur locally, edge devices in the network can enable near-real-time data analysis in order to make data-driven decisions Energy : Clustering methods have been known to be more energy efficient when it comes to data transmission and processing (Loganathan & Arumugan, 2021).

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Pickl AI

AUGUST 22, 2024

First released in 2016, it quickly gained traction due to its intuitive design and robust capabilities. In industry, it powers applications in computer vision, natural language processing, and reinforcement learning. It excels in image classification, natural language processing, and time series forecasting applications.

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Data Science Blog

FEBRUARY 23, 2023

Presumably due to this fact, Andrew Ng, in his presentation in NeurIPS 2016, gave a rough and abstract predictions of how transfer learning in machine learning would make commercial success like white lines in the figure below. My point is, the more data you have, and the bigger computation resource you have, the better performance you get.

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ML Review

FEBRUARY 26, 2018

Following its successful adoption in computer vision and voice recognition, DL will continue to be applied in the domain of natural language processing (NLP). In Proceedings of The First International Workshop on Machine Learning in Spoken Language Processing. [5] 2016 [6] Li J, Monroe W, Ritter A, et al.

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AWS Machine Learning Blog

FEBRUARY 28, 2023

Use natural language processing (NLP) in Amazon HealthLake to extract non-sensitive data from unstructured blobs. The high-level steps involved in the solution are as follows: Use AWS Step Functions to orchestrate the health data anonymization pipeline. Perform one-hot encoding with Amazon SageMaker Data Wrangler.

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How to Learn Machine Learning

DECEMBER 4, 2022

In 2016, Google released an open-source software called AutoML. Another way AI is being used to write code is through the use of natural language processing (NLP). NLP is a type of AI that can understand human language and convert it into code. One recent example of the usage of Ai is in the field of code writing.

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Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Foundations of Statistical Natural Language Processing [M]. Depending on the data they are provided, different classifiers may perform better or worse (eg. Uysal and Gunal, 2014). Manning C. and Schutze H.,

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Dataconomy

FEBRUARY 22, 2023

The decisive victory comes seven years after the AI system AlphaGo, devised by Google-owned research company DeepMind, defeated the world Go champion Lee Sedol by four games to one in 2016. As technology continues to evolve, we can anticipate more breakthroughs in areas such as natural language processing and computer vision.

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ODSC - Open Data Science

OCTOBER 15, 2023

Ikigai Labs Ikigai Labs is a company that provides a platform for building and managing natural language processing models. Outerbounds Founded in 2016, Outerbounds is a company that provides a platform for building and managing anomaly detection models.

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Explosion

NOVEMBER 21, 2019

In 2016 we trained a sense2vec model on the 2015 portion of the Reddit comments corpus, leading to a useful library and one of our most popular demos. from_disk("/path/to/s2v_reddit_2015_md") nlp.add_pipe(s2v) doc = nlp("A sentence about natural language processing.") That work is now due for an update. assert doc[3:6].text

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AWS Machine Learning Blog

APRIL 18, 2023

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

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Explosion

FEBRUARY 12, 2017

The Quora dataset is an example of an important type of Natural Language Processing problem: text-pair classification. Tackström, Oscar; Das, Dipanjan; Uszkoreit, Jakob (2016) A large annotated corpus for learning natural language inference Bowman, Samuel R.;

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Mlearning.ai

MARCH 9, 2023

Generative adversarial networks-based adversarial training for natural language processing. 2018; Papernot et al., Towards deep learning models resistant to adversarial attacks. arXiv preprint arXiv:1706.06083. Papernot, N., McDaniel, P., Fredrikson, M., B., & Swami, A. Sitawarin, C., Chen, Y., & Du, B. 501–509).

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Pickl AI

OCTOBER 1, 2024

Read More: Top 7 Generative AI Use Cases and Application Hugging Face Hugging Face is a New York-based AI research company that is best known for its work on open-source natural language processing (NLP) models.

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Explosion

AUGUST 1, 2019

Transformers and transfer-learning Natural Language Processing (NLP) systems face a problem known as the “knowledge acquisition bottleneck”. 2019) have shown that a transformer models trained on only 1% of the IMDB sentiment analysis data (just a few dozen examples) can exceed the pre-2016 state-of-the-art.

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DrivenData Labs

FEBRUARY 3, 2025

His research focuses on applying natural language processing techniques to extract information from unstructured clinical and medical texts, especially in low-resource settings. I love participating in various competitions involving deep learning, especially tasks involving natural language processing or LLMs.

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