Data Science Dojo

SEPTEMBER 8, 2023

Descriptive analytics involves summarizing historical data to extract insights into past events. Diagnostic analytics goes further, aiming to uncover the root causes behind these events. ML encompasses a range of algorithms that enable computers to learn from data without explicit programming. Streamline operations.

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Google Research AI blog

MAY 23, 2023

However, with machine learning (ML), we have an opportunity to automate and streamline the code review process, e.g., by proposing code changes based on a comment’s text. As of today, code-change authors at Google address a substantial amount of reviewer comments by applying an ML-suggested edit. 3-way-merge UX in IDE.

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AWS Machine Learning Blog

MARCH 17, 2025

Large language models (LLMs) have revolutionized the field of natural language processing, enabling machines to understand and generate human-like text with remarkable accuracy. However, despite their impressive language capabilities, LLMs are inherently limited by the data they were trained on.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

From gaming and entertainment to education and corporate events, live streams have become a powerful medium for real-time engagement and content consumption. By offering real-time translations into multiple languages, viewers from around the world can engage with live content as if it were delivered in their first language.

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Data Science Dojo

OCTOBER 31, 2024

For instance, Berkeley’s Division of Data Science and Information points out that entry level data science jobs remote in healthcare involves skills in NLP (Natural Language Processing) for patient and genomic data analysis, whereas remote data science jobs in finance leans more on skills in risk modeling and quantitative analysis.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. And although generative AI has appeared in previous events, this year we’re taking it to the next level. Visit the session catalog to learn about all our generative AI and ML sessions.

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AWS Machine Learning Blog

FEBRUARY 6, 2025

These variables often involve complex sequences of events, combinations of occurrences and non-occurrences, as well as detailed numeric calculations or categorizations that accurately reflect the diverse nature of patient experiences and medical histories. About the Authors Javier Beltrn is a Senior Machine Learning Engineer at Aetion.

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Heartbeat

FEBRUARY 8, 2023

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

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Flipboard

JANUARY 14, 2025

Moreover, interest in small language models (SLMs) that enable resource-constrained devices to perform complex functionssuch as natural language processing and predictive automationis growing.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Amazon SageMaker Feature Store provides an end-to-end solution to automate feature engineering for machine learning (ML). For many ML use cases, raw data like log files, sensor readings, or transaction records need to be transformed into meaningful features that are optimized for model training. SageMaker Studio set up.

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Heartbeat

JULY 18, 2023

Source: Author Natural Language Processing (NLP) is a field of study focused on allowing computers to understand and process human language. There are many different NLP techniques and tools available, including the R programming language. keep_active: determines whether to keep the experiment active or not.

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Heartbeat

FEBRUARY 9, 2023

Photo by Brooks Leibee on Unsplash Introduction Natural language processing (NLP) is the field that gives computers the ability to recognize human languages, and it connects humans with computers. SpaCy is a free, open-source library written in Python for advanced Natural Language Processing.

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Dataconomy

DECEMBER 18, 2024

Machine Learning (ML) , a subset of AI, enables systems to learn and improve from data without explicit programming, making decisions based on patterns and large datasets. Deep Learning (DL) , a branch of ML, uses artificial neural networks to model complex relationships and solve problems with large datasets.

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Dataconomy

JUNE 16, 2023

In order to prevent data loss, its system continuously monitors staff and offers event-driven security awareness training. The business’s solution makes use of AI to continually monitor personnel and deliver event-driven security awareness training in order to prevent data theft. How to use Gamme AI?

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Heartbeat

MARCH 22, 2023

Learn NLP data processing operations with NLTK, visualize data with Kangas , build a spam classifier, and track it with Comet Machine Learning Platform Photo by Stephen Phillips — Hostreviews.co.uk on Unsplash At its core, the discipline of Natural Language Processing (NLP) tries to make the human language “palatable” to computers.

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Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. This integration combines visual features extracted from images with language models to generate descriptive and contextually relevant captions.

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Dataconomy

MAY 2, 2023

The machine learning systems developed by Machine Learning Engineers are crucial components used across various big data jobs in the data processing pipeline. Additionally, Machine Learning Engineers are proficient in implementing AI or ML algorithms. Is ML engineering a stressful job?

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AWS Machine Learning Blog

FEBRUARY 6, 2024

Pharmaceutical companies sell a variety of different, often novel, drugs on the market, where sometimes unintended but serious adverse events can occur. These events can be reported anywhere, from hospitals or at home, and must be responsibly and efficiently monitored.

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AWS Machine Learning Blog

NOVEMBER 27, 2023

In this post, we demonstrate how business analysts and citizen data scientists can create machine learning (ML) models, without any code, in Amazon SageMaker Canvas and deploy trained models for integration with Salesforce Einstein Studio to create powerful business applications. After your model begins building, you can leave the page.

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AWS Machine Learning Blog

MARCH 18, 2025

The LLM analyzes the text, identifying key information relevant to the clinical trial, such as patient symptoms, adverse events, medication adherence, and treatment responses. These insights can include: Potential adverse event detection and reporting. Identification of protocol deviations or non-compliance. No problem!

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AWS Machine Learning Blog

FEBRUARY 7, 2025

Our commitment to innovation led us to a pivotal challenge: how to harness the power of machine learning (ML) to further enhance our competitive edge while balancing this technological advancement with strict data security requirements and the need to streamline access to our existing internal resources.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

If the question was Whats the schedule for AWS events in December?, AWS usually announces the dates for their upcoming # re:Invent event around 6-9 months in advance. Chaithanya Maisagoni is a Senior Software Development Engineer (AI/ML) in Amazons Worldwide Returns and ReCommerce organization.

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AWS Machine Learning Blog

JUNE 5, 2025

In this post, we share how Radial optimized the cost and performance of their fraud detection machine learning (ML) applications by modernizing their ML workflow using Amazon SageMaker. Businesses need for fraud detection models ML has proven to be an effective approach in fraud detection compared to traditional approaches.

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AWS Machine Learning Blog

MARCH 5, 2025

Chronos is founded on a key insight: both LLMs and time series forecasting aim to decode sequential patterns to predict future events. This parallel allows us to treat time series data as a language to be modeled by off-the-shelf transformer architectures. In addition, he builds and deploys AI/ML models on the AWS Cloud.

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NYU Center for Data Science

MARCH 15, 2023

The NYU AI School grew from a 3-day workshop that took place in October 2019, with the first week-long event launched in February 2021. Unlike many other events, no programming experience is required to attend. The program is organized by students from NYU Data Science, Courant Institute, and other departments.

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AWS Machine Learning Blog

MARCH 13, 2025

The emergence of generative AI agents in recent years has contributed to the transformation of the AI landscape, driven by advances in large language models (LLMs) and natural language processing (NLP). In this approach, the workflow emerges from the collective behavior of the agents reacting to events asynchronously.

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The MLOps Blog

APRIL 5, 2023

In this comprehensive guide, we’ll explore the key concepts, challenges, and best practices for ML model packaging, including the different types of packaging formats, techniques, and frameworks. Best practices for ml model packaging Here is how you can package a model efficiently.

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AWS Machine Learning Blog

AUGUST 28, 2023

Because most of the students were unfamiliar with machine learning (ML), they were given a brief tutorial illustrating how to set up an ML pipeline: how to conduct exploratory data analysis, feature engineering, model building, and model evaluation, and how to set up inference and monitoring.

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IBM Journey to AI blog

AUGUST 12, 2024

AIOPs refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and automate various aspects of IT operations (ITOps). ML technologies help computers achieve artificial intelligence. However, they differ fundamentally in their purpose and level of specialization in AI and ML environments.

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AWS Machine Learning Blog

JANUARY 21, 2025

Analyzing past trends while accounting for impacts ranging from seasons to world events provides insights to guide business planning. In this post, we show you how Amazon Web Services (AWS) helps in solving forecasting challenges by customizing machine learning (ML) models for forecasting. One of these methods is quantiles.

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Dataconomy

AUGUST 3, 2023

They’ve long used AI’s little brother Machine Learning (ML) for demand and price management in the airline, hotel, and transport industries. ML and AI are already working to benefit travel companies Online travel platforms and service providers have been using ML for years, even if travelers aren’t aware of this. AI is (merely!)

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BAIR

MARCH 11, 2024

Their work at BAIR, ranging from deep learning, robotics, and natural language processing to computer vision, security, and much more, has contributed significantly to their fields and has had transformative impacts on society. Currently, I am working on Large Language Model (LLM) based autonomous agents.

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AWS Machine Learning Blog

NOVEMBER 21, 2024

Event extraction: Extracts the bucket name and PDF key from the incoming event payload. It receives the event and context parameters. The code snippet that follows provides a sample of the code used to extract the images from the PDF file and save them back to S3. Directory creation: Ensures the directory for images exists.

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Data Science Dojo

FEBRUARY 2, 2023

To create a simple game using Pygame, you will need to understand the basics of game development such as game loop, event handling, and game mechanics. To build a chatbot using Python, you will need to use a combination of NLP and ML techniques.

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AWS Machine Learning Blog

SEPTEMBER 27, 2023

can process scanned PDFs without manual review. The solution also uses Amazon Comprehend , which uses natural language processing (NLP) to identify and extract key entities from the ADR documents, such as name, date of birth, and date of service.

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AWS Machine Learning Blog

DECEMBER 1, 2023

As organizations scale the adoption of machine learning (ML), they are looking for efficient and reliable ways to deploy new infrastructure and onboard teams to ML environments. For example, MLOps engineers typically perform model deployment activities, whereas data scientists perform ML training and validation activities.

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Heartbeat

JUNE 5, 2023

Without proper tracking, optimization, and collaboration tools, ML practitioners can quickly become overwhelmed and lose track of their progress. Comet’s integrations are modular and customizable, enabling teams to incorporate new approaches and tools to their ML platforms. This is where Comet comes in.

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