NYU Center for Data Science

JULY 18, 2023

MaD & MaD+ The Math and Data (MaD) group is a collaboration between CDS and the NYU Courant Institute of Mathematical Sciences. And how can we best use insights from natural intelligence to develop new, more powerful machine intelligence technologies that more fruitfully interact with us?”

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Women in Big Data

DECEMBER 13, 2023

The Bay Area Chapter of Women in Big Data (WiBD) hosted its second successful episode on the NLP (Natural Language Processing), Tools, Technologies and Career opportunities. Currently based in Germany, she possesses extensive experience in developing data-intensive applications leveraging NLP, data science, and data analytics.

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Dataconomy

APRIL 3, 2023

Artificial intelligence, commonly referred to as AI , is the field of computer science that focuses on the development of intelligent machines that can perform tasks that would typically require human intervention. ML models are designed to learn from data and make predictions or decisions based on that data.

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Dataconomy

APRIL 3, 2023

Artificial intelligence, commonly referred to as AI , is the field of computer science that focuses on the development of intelligent machines that can perform tasks that would typically require human intervention. ML models are designed to learn from data and make predictions or decisions based on that data.

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NYU Center for Data Science

MARCH 15, 2023

The program is organized by students from NYU Data Science, Courant Institute, and other departments. It is supported by the NYU ML² Machine Learning for Language Lab , a team of researchers developing machine-learning methods for natural language processing (NLP) affiliated with the CILVR Lab , and the Center for Data Science.

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Dataconomy

MARCH 14, 2023

In recent years, natural language processing and conversational AI have gained significant attention as technologies that are transforming the way we interact with machines and each other. Natural language processing involves the application of artificial intelligence to comprehend and respond to human language.

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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. Computer science, math, statistics, programming, and software development are all skills required in NLP projects.

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Google Research AI blog

APRIL 19, 2023

This transformative potential requires us to be responsible not only in how we advance our technology, but also in how we envision which technologies to build, and how we assess the social impact AI and ML-enabled technologies have on the world. Below, we share examples of our approach to Responsible AI and where we are headed in 2023.

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AWS Machine Learning Blog

OCTOBER 6, 2023

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. One such component is a feature store, a tool that stores, shares, and manages features for machine learning (ML) models.

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Towards AI

AUGUST 16, 2023

In fact, AI/ML graduate textbooks do not provide a clear and consistent description of the AI software engineering process. Therefore, I thought it would be helpful to give a complete description of the AI engineering process or AI Process, which is described in most AI/ML textbooks [5][6].

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AWS Machine Learning Blog

NOVEMBER 22, 2023

The IDP Well-Architected Custom Lens follows the AWS Well-Architected Framework, reviewing the solution with six pillars with the granularity of a specific AI or machine learning (ML) use case, and providing the guidance to tackle common challenges. Model monitoring The performance of ML models is monitored for degradation over time.

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Dataconomy

FEBRUARY 22, 2023

The systems can only “understand” specific situations they have been exposed to in the past and are unable to generalize in a way that humans find easy, said Stuart Russell, a computer science professor at the University of California, Berkeley.

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Data Science Dojo

FEBRUARY 2, 2023

It is widely used in numerous fields, from data science and machine learning to web development and game development. It is a widely used programming language in computer science. To build a chatbot using Python, you will need to use a combination of NLP and ML techniques.

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Pickl AI

APRIL 25, 2023

Consequently, ML algorithms can be further divided into two categories, supervised and unsupervised. Neural networks have been effectively useful to fulfill various tasks, including audio and image identification, natural language processing, and autonomous vehicle control. NLP stands for Natural Language Processing.

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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? But exactly what is NLP , and how can it facilitate legal discovery?

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AWS Machine Learning Blog

NOVEMBER 22, 2023

An intelligent document processing (IDP) project usually combines optical character recognition (OCR) and natural language processing (NLP) to read and understand a document and extract specific entities or phrases. She has extensive experience in machine learning with a PhD degree in computer science.

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ODSC - Open Data Science

JUNE 7, 2023

Leverage Compound Sparsity to Achieve the Fastest Inference Performance on CPUs: Damian Bogunowicz and Konstantin Gulin | Machine Learning Engineers | Neural Magic Few-shot Learning for Natural Language Understanding: Helen Yannakoudakis | Assistant Professor | King’s College London Probabilistic Machine Learning for Finance and Investing: Deepak Kanungo (..)

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AWS Machine Learning Blog

NOVEMBER 22, 2023

An IDP pipeline usually combines optical character recognition (OCR) and natural language processing (NLP) to read and understand a document and extract specific terms or words. Keep documentation of processing rules thorough and up to date, fostering a transparent environment for all stakeholders.

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AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. GitHub serves as a centralized location to store, version, and manage your ML code base.

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Mlearning.ai

MAY 23, 2023

Here are a few courses you can check out — AI for Medicine Specialization Natural Language Processing Specialization Generative Adversarial Networks (GANs) Specialization Educational Background A Bachelor’s degree in a quantitative field like computer science, mathematics, statistics, or engineering is often the minimum requirement.

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Mlearning.ai

SEPTEMBER 2, 2023

It made me realize that I want to major in exactly the Machine Learning field during my university years instead of just computer science (in general) which consists of the other 28 subfields apart from Machine Learning. That was when my interest in the subject grew deep down in my soul. I said, “Sure!

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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. Once the system is trained, it can use its knowledge to perform various tasks, such as image recognition, language translation, or speech synthesis.

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IBM Journey to AI blog

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML). The development and use of these models explain the enormous amount of recent AI breakthroughs.

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AWS Machine Learning Blog

APRIL 18, 2023

To improve this experience for its members, we at RallyPoint wanted to explore how machine learning (ML) could help. If you’d like to collaborate with experts to bring ML solutions to your organization, contact the Amazon ML Solutions Lab. Matthew Rhodes is a Data Scientist working in the Amazon ML Solutions Lab.

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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. Lensch, H. A., & Akata, Z.

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Dataconomy

MARCH 13, 2023

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. However, the process of creating AI can seem daunting to those who are unfamiliar with the technicalities involved. What is required to build an AI system?

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Technical challenges with multi-modal data further include the complexity of integrating and modeling different data types, the difficulty of combining data from multiple modalities (text, images, audio, video), and the need for advanced computer science skills and sophisticated analysis tools. WWW: $85.91 DDD: $9.82

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AWS Machine Learning Blog

APRIL 27, 2023

Solution overview With the onset of large language models, the field has seen tremendous progress on various natural language processing (NLP) benchmarks. He has a PhD in computer science at Cornell University. Nitish Joshi was an applied science intern at AWS AI, Amazon.

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IBM Journey to AI blog

JULY 6, 2023

Data science solves a business problem by understanding the problem, knowing the data that’s required, and analyzing the data to help solve the real-world problem. Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. What is machine learning?

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AWS Machine Learning Blog

FEBRUARY 14, 2023

Amazon Kendra is an intelligent search service powered by machine learning (ML). It indexes the documents stored in a wide range of repositories and finds the most relevant document based on the keywords or natural language questions the user has searched for. In our example, we have 2 users, User1 and User 2.

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ML @ CMU

FEBRUARY 24, 2023

All language models (LMs) are frozen. Figure 1 : Overview of RL Prompt for discrete prompt optimization. We build our policy network by training a task-specific multi-layer perceptron (MLP) network inserted into a frozen pre-trained LM.

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AWS Machine Learning Blog

AUGUST 14, 2023

SageMaker JumpStart also provides solution templates that set up infrastructure for common use cases, and executable example notebooks for machine learning (ML) with SageMaker. In recent years, ML techniques have become increasingly popular to enhance search. Mia Chang is an ML Specialist Solutions Architect for Amazon Web Services.

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Heartbeat

MARCH 5, 2024

Whether you're a seasoned machine learning practitioner or a curious enthusiast, this article aims to provide insights into how image enhancement can be an engaging and effective strategy for advancing computer vision applications. It seeks to mimic perception and comprehension of the visual world by the human Toem.

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IBM Journey to AI blog

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language.

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AWS Machine Learning Blog

NOVEMBER 7, 2023

Amazon Kendra with foundational LLM Amazon Kendra is an advanced enterprise search service enhanced by machine learning (ML) that provides out-of-the-box semantic search capabilities. Semantic understanding – The ML capabilities of Amazon Kendra ensure that retrieval is based on deep semantic understanding and not just keyword matches.

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DrivenData Labs

MARCH 30, 2023

His interests are in privacy-preserving machine learning, particularly in the areas of differential privacy, ML security, and federated learning. Mayank Shah is a Data Science Consultant at ZS and holds a Bachelor’s in Technology for Computer Science from Maharaja Agrasen Institute of Technology.

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Chatbots Life

SEPTEMBER 11, 2023

This limitation has paved the way for more advanced solutions that harness the power of Natural Language Processing (NLP). This has spurred the development of more advanced solutions powered by Natural Language Processing (NLP) that offer a more comprehensive approach to language-related tasks.

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