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. We are hearing about NLP, LLMs, ChatGPT and Generative AI a lot ! Computational Linguistics is rule based modeling of natural languages.

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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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Dataconomy

MAY 25, 2023

By harnessing the power of AI in IoT, we can create intelligent ecosystems where devices seamlessly communicate, collaborate, and make intelligent choices to improve our lives. Let’s explore the fascinating intersection of these two technologies and understand how AI enhances the functionalities of IoT.

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ODSC - Open Data Science

JUNE 7, 2023

If you are unable to join us at the Tobacco Dock this June, we’ll be hosting lots of engaging training sessions, workshops, and talks on our virtual platform. Check out our confirmed sessions below.

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AWS Machine Learning Blog

FEBRUARY 2, 2024

One of the most useful application patterns for generative AI workloads is Retrieval Augmented Generation (RAG). Embeddings capture the information content in bodies of text, allowing natural language processing (NLP) models to work with language in a numeric form.

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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. Companies are finding NLP to be one of the best applications of AI regardless of industry.

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AWS Machine Learning Blog

APRIL 19, 2023

Business requirements We are the US squad of the Sportradar AI department. Since 2018, our team has been developing a variety of ML models to enable betting products for NFL and NCAA football. These models are then pushed to an Amazon Simple Storage Service (Amazon S3) bucket using DVC, a version control tool for ML models.

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ODSC - Open Data Science

AUGUST 15, 2023

Advancements in data science and AI are coming at a lightning-fast pace. Full-Stack Machine Learning for Data Scientists Hugo Bowne-Anderson, PhD | Head of Data Science Evangelism and Marketing | Outerbounds This session will address the issue of how to make the life cycle of a machine learning project a repeatable process.

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Dataconomy

MARCH 13, 2023

The creation of artificial intelligence (AI) has long been a dream of scientists, engineers, and innovators. With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. How to create an artificial intelligence?

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Mlearning.ai

AUGUST 2, 2023

Harnessing the Power of Diverse Hardware One of the key advantages of Fully Sharded Data Parallelism is its ability to leverage a mix of powerful GPUs, TPUs, or other specialised hardware in training clusters. Embrace the power of Fully Sharded Data Parallelism and unlock the full potential of your language models.

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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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Mlearning.ai

MARCH 6, 2023

A Beginner’s Guide to FAISS, use-cases, Mathematical foundations & implementation FAISS (Facebook AI Similarity Search) is an open-source library developed by Facebook AI Research (FAIR) for high-dimensional data similarity search and clustering.

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phData

DECEMBER 7, 2023

A common example is word embeddings in natural language processing. However, the Generative AI space is rapidly evolving, and you may need to experiment with different models to try to improve performance or search relevance. If this is the case, you can find the latest developments on the Hugging Face Leaderboard.

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AWS Machine Learning Blog

MAY 3, 2023

For any machine learning (ML) problem, the data scientist begins by working with data. This includes gathering, exploring, and understanding the business and technical aspects of the data, along with evaluation of any manipulations that may be needed for the model building process.

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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

APRIL 18, 2024

While AGI remains theoretical, organizations can take proactive steps to prepare for its arrival by building a robust data infrastructure and fostering a collaborative environment where humans and AI work together seamlessly. NLP techniques help them parse the nuances of human language, including grammar, syntax and context.

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Mlearning.ai

JANUARY 27, 2023

The technique is commonly used in natural language processing, computer vision, and information retrieval. To do this, we can use the Word2Vec function of gensim, which is a popular Python library for natural language processing.

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Dataconomy

FEBRUARY 28, 2023

Deep learning models have emerged as a powerful tool in the field of ML, enabling computers to learn from vast amounts of data and make decisions based on that learning. This has enabled significant advancements in areas such as computer vision, speech recognition, natural language processing, and more. How do LSTMs work?

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The MLOps Blog

JANUARY 25, 2023

Sentiment analysis, commonly referred to as opinion mining/sentiment classification, is the technique of identifying and extracting subjective information from source materials using computational linguistics , text analysis , and natural language processing. positive, negative, neutral). Words like “Descent”, “Average”, etc.

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PyImageSearch

MARCH 30, 2023

What is Machine Learning A Closer Look at Machine Learning Machine learning (ML) revolves around creating algorithms and related systems that learn behavior strategies in specific environments using instructions and training data sets.

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AWS Machine Learning Blog

FEBRUARY 12, 2024

Sharing in-house resources with other internal teams, the Ranking team machine learning (ML) scientists often encountered long wait times to access resources for model training and experimentation – challenging their ability to rapidly experiment and innovate. If it shows online improvement, it can be deployed to all the users.

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Mlearning.ai

JUNE 23, 2023

Options (Free vs Paid) Closing Introduction In today’s increasingly globalized world, the ability to communicate in multiple languages has become a highly valuable skill. Language Models (LLMs) have revolutionized the field of natural language processing, bringing unprecedented advancements in understanding and generating human-like text.

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AWS Machine Learning Blog

AUGUST 14, 2023

Amazon SageMaker JumpStart is a machine learning (ML) hub offering algorithms, models, and ML solutions. Question answering Context: NLP Cloud was founded in 2021 when the team realized there was no easy way to reliably leverage Natural Language Processing in production. Question: When was NLP Cloud founded?

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AWS Machine Learning Blog

MAY 25, 2023

One of the most common applications of generative AI and large language models (LLMs) in an enterprise environment is answering questions based on the enterprise’s knowledge corpus. Amazon Lex provides the framework for building AI based chatbots. Solution overview We use the SageMaker docs as the knowledge corpus for this post.

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Data Science Dojo

MAY 10, 2024

Hence, acting as a translator it converts human language into a machine-readable form. Their impact on ML tasks has made them a cornerstone of AI advancements. These embeddings when particularly used for natural language processing (NLP) tasks are also referred to as LLM embeddings.

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Pickl AI

AUGUST 3, 2023

These algorithms have shown remarkable success in solving a wide range of complex tasks, such as image recognition, natural language processing, speech recognition, and more. SOMs have been used in data clustering, data compression, and anomaly detection. Read Blog: How to build a Machine Learning Model?

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Pickl AI

NOVEMBER 8, 2023

The cheat sheet helps you select the right one for your specific task, be it regression, classification, or clustering. Can I use Scikit-Learn for natural language processing (NLP)? Yes, Scikit-Learn offers tools for basic text processing and feature extraction, making it suitable for some NLP tasks.

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Pickl AI

MAY 10, 2023

ML algorithms fall into various categories which can be generally characterised as Regression, Clustering, and Classification. While Classification is an example of directed Machine Learning technique, Clustering is an unsupervised Machine Learning algorithm. It can also be used for determining the optimal number of clusters.

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ODSC - Open Data Science

JANUARY 29, 2024

The role of prompt engineer has attracted massive interest ever since Business Insider released an article last spring titled “ AI ‘Prompt Engineer Jobs: $375k Salary, No Tech Backgrund Required.” While many of us dream of having a job in AI that doesn’t require knowing AI tools and skillsets, that’s not actually the case.

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AWS Machine Learning Blog

APRIL 1, 2024

Machine learning (ML) research has proven that large language models (LLMs) trained with significantly large datasets result in better model quality. Distributed model training requires a cluster of worker nodes that can scale. The following figure shows how FSDP works for two data parallel processes.

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

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AWS Machine Learning Blog

MAY 2, 2023

JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. JumpStart provides many pre-trained language models called foundation models that can help you perform tasks such as article summarization, question answering, and conversation generation and image generation.

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AWS Machine Learning Blog

APRIL 29, 2024

To build a production-grade AI system today (for example, to do multilingual sentiment analysis of customer support conversations), what are the primary technical challenges? Historically, natural language processing (NLP) would be a primary research and development expense. The following figure illustrates this workflow.

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Flipboard

NOVEMBER 17, 2023

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. This type of data is often used in ML and artificial intelligence applications.

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AWS Machine Learning Blog

MAY 1, 2024

Large language models (LLMs) are making a significant impact in the realm of artificial intelligence (AI). For more information on Trainium Accelerator chips, refer to Achieve high performance with lowest cost for generative AI inference using AWS Inferentia2 and AWS Trainium on Amazon SageMaker.

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Snorkel AI

MAY 10, 2023

He presented “Data and Manual Annotation Monitoring for Training Data Management” at Snorkel AI’s The Future of Data-Centric AI event in 2022. This is a diagnostic method that came out of the Allen Institute for AI, or AI2, by Swayamdipta et al., William Huang is a senior data scientist at Capital One. They’re so fluid.

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Snorkel AI

MAY 10, 2023

He presented “Data and Manual Annotation Monitoring for Training Data Management” at Snorkel AI’s The Future of Data-Centric AI event in 2022. This is a diagnostic method that came out of the Allen Institute for AI, or AI2, by Swayamdipta et al., William Huang is a senior data scientist at Capital One. They’re so fluid.

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