Becoming Human

MARCH 16, 2023

The applications of graph classification are numerous, and they range from determining whether a protein is an enzyme or not in bioinformatics to categorizing documents in natural language processing (NLP) or social network analysis, among other things. How do Graph Neural Networks work?

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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

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

MAY 1, 2024

In high performance computing (HPC) clusters, such as those used for deep learning model training, hardware resiliency issues can be a potential obstacle. It then replaces any faulty instances, if necessary, to make sure the training script starts running on a healthy cluster of instances.

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Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud.

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ODSC - Open Data Science

JUNE 7, 2023

Gözde Gül Şahin | Assistant Professor, KUIS AI Fellow | KOC University Fraud Detection with Machine Learning: Laura Mitchell | Senior Data Science Manager | MoonPay Deep Learning and Comparisons between Large Language Models: Hossam Amer, PhD | Applied Scientist | Microsoft Multimodal Video Representations and Their Extension to Visual Language Navigation: (..)

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Pickl AI

JULY 12, 2024

Deep Learning has been used to achieve state-of-the-art results in a variety of tasks, including image recognition, Natural Language Processing, and speech recognition. Natural Language Processing (NLP) This is a field of computer science that deals with the interaction between computers and human language.

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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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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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IBM Journey to AI blog

JULY 6, 2023

These computer science terms are often used interchangeably, but what differences make each a unique technology? Natural language processing (NLP) and computer vision, which let companies automate tasks and underpin chatbots and virtual assistants such as Siri and Alexa, are examples of ANI.

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ODSC - Open Data Science

JANUARY 7, 2025

Just as a writer needs to know core skills like sentence structure and grammar, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and soon. Theyre looking for people who know all related skills, and have studied computer science and software engineering.

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Flipboard

JULY 10, 2023

time series or natural language processing tasks). Feature Learning Autoencoders can learn meaningful features from input data, which can be used for downstream machine learning tasks like classification, clustering, or regression. Or requires a degree in computer science? That’s not the case.

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AWS Machine Learning Blog

OCTOBER 30, 2024

These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval. Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

As an example, in the following figure, we separate Cover 3 Zone (green cluster on the left) and Cover 1 Man (blue cluster in the middle). We design an algorithm that automatically identifies the ambiguity between these two classes as the overlapping region of the clusters. Outside of work, he enjoys soccer and video games.

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AWS Machine Learning Blog

JANUARY 20, 2023

Christopher earned his Bachelor of Science in Computer Science from Northeastern Illinois University. Sam has a Bachelor of Science in Computer Science and a Bachelor of Science in Mathematics from the University of Texas at Austin. For pricing information, visit Amazon SageMaker Pricing.

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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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Pickl AI

SEPTEMBER 18, 2024

Tech companies, they might focus on developing recommendation systems, fraud detection algorithms, or Natural Language Processing tools. Most professionals in this field start with a bachelor’s degree in computer science, Data Science, mathematics, or a related discipline. Platforms like Pickl.AI

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Pickl AI

JULY 18, 2023

Here are the key steps to embark on the path towards becoming an AI Architect: Acquire a Strong Foundation Start by building a solid foundation in computer science, mathematics, and statistics. Explore topics such as regression, classification, clustering, neural networks, and natural language processing.

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Google Research AI blog

FEBRUARY 28, 2023

For example, supporting equitable student persistence in computing research through our Computer Science Research Mentorship Program , where Googlers have mentored over one thousand students since 2018 — 86% of whom identify as part of a historically marginalized group.

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Pickl AI

NOVEMBER 5, 2024

It combines various techniques from statistics, mathematics, computer science, and domain expertise to interpret complex data sets. AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision.

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Pickl AI

JANUARY 13, 2025

Includes statistical natural language processing techniques. Each concept is supported by algorithms, mathematical models, and case studies, making it ideal for readers with a basic understanding of mathematics or computer science. Key Features: Explains AI algorithms like clustering and regression.

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ODSC - Open Data Science

APRIL 21, 2023

By translating responses to high-dimensional vector embeddings, clustering algorithms can group the data into discrete sets of documents that share a semantic similarity. LLMs are trained on much larger datasets, which allows them to contain richer information about how words are typically used together.

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Pickl AI

SEPTEMBER 12, 2024

Artificial Intelligence (AI): A branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities.

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Data Analyst Data Science Machine Learning Machine Learning 52

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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AWS Machine Learning Blog

MAY 24, 2023

Natural language processing (NLP) is one of the recent developments in IDP that has improved accuracy and user experience. As an alternative, you can use FAISS , an open-source vector clustering solution for storing vectors. However, despite these advances, there are still challenges to overcome.

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Snorkel AI

MARCH 31, 2023

Deep learning became the new focus, first led by the advance in computer vision, then followed by natural language processing. Training a tens- or hundreds-billion parameter model, using close to a terabyte worth of data, pretty much requires a dedicated supercomputer scale cluster for weeks or months.

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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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Pickl AI

SEPTEMBER 23, 2024

Understanding Data Science Data Science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. It combines principles from statistics, mathematics, computer science, and domain-specific knowledge to analyse and interpret complex data.

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DrivenData Labs

FEBRUARY 3, 2025

Recently, I became interested in machine learning, so I was enrolled in the Yandex School of Data Analysis and Computer Science Center. His research focuses on applying natural language processing techniques to extract information from unstructured clinical and medical texts, especially in low-resource settings.

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DrivenData Labs

DECEMBER 7, 2023

Solvers submitted a wide range of methodologies to this end, including using open-source and third party LLMs (GPT, LLaMA), clustering (DBSCAN, K-Means), dimensionality reduction (PCA), topic modeling (LDA, BERT), sentence transformers, semantic search, named entity recognition, and more. and DistilBERT.

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AWS Machine Learning Blog

FEBRUARY 25, 2025

Model invocation We use Anthropics Claude 3 Sonnet model for the natural language processing task. This LLM model has a context window of 200,000 tokens, enabling it to manage different languages and retrieve highly accurate answers. temperature This parameter controls the randomness of the language models output.

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DrivenData Labs

DECEMBER 10, 2023

or GPT-4 arXiv, OpenAlex, CrossRef, NTRS lgarma Topic clustering and visualization, paper recommendation, saved research collections, keyword extraction GPT-3.5 He also boasts several years of experience with Natural Language Processing (NLP). bge-small-en-v1.5 What motivated you to compete in this challenge?

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

PBAs, such as graphics processing units (GPUs), have an important role to play in both these phases. The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. In FSI, non-time series workloads are also underpinned by algorithms that can be parallelized.

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AWS Machine Learning Blog

JUNE 27, 2024

For training, we chose to use a cluster of trn1.32xlarge instances to take advantage of Trainium chips. We used a cluster of 32 instances in order to efficiently parallelize the training. We also used AWS ParallelCluster to manage cluster orchestration. Before moving to industry, Tahir earned an M.S.

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DrivenData Labs

DECEMBER 11, 2024

A number of breakthroughs are enabling this progress, and here are a few key ones: Compute and storage - The increased availability of cloud compute and storage has made it easier and cheaper to get the compute resources organizations need. Deep learning - It is hard to overstate how deep learning has transformed data science.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

She is a technologist with a PhD in Computer Science, a master’s degree in Education Psychology, and years of experience in data science and independent consulting in AI/ML. This post proposes Auto-CoT, which samples questions with diversity and generates reasoning chains to construct the demonstrations.

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AWS Machine Learning Blog

AUGUST 30, 2024

The 8-billion-parameter model integrates grouped-query attention (GQA) for improved processing of longer data sequences, enhancing real-world application performance. Training involved a dataset of over 15 trillion tokens across two GPU clusters, significantly more than Meta Llama 2.

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