Marktechpost

JUNE 9, 2024

Explainable AI (xAI) methods, such as saliency maps and attention mechanisms, attempt to clarify these models by highlighting key ECG features. Future applications include other biosignals and improving big data cardiac screening through automated, trustworthy diagnostics. Check out the Paper.

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Pickl AI

FEBRUARY 17, 2025

This automation not only increases efficiency but also enhances the accuracy of data interpretation, allowing organisations to focus on more strategic tasks. Scalability Machine Learning techniques are designed to handle vast amounts of data, making them well-suited for big data applications.

Machine Learning 52

Machine Learning Algorithm Explainability Data Quality 52

ODSC - Open Data Science

JUNE 1, 2023

With augmented analytics (and embedded insights), anyone can become a citizen data scientist, regardless of their advanced analytics expertise. Big Data and the Blue Economy Since the concept of the blue economy relies on managing and developing something so broad, utilizing big data may be necessary.

ML 52

ML Data Scientist Big Data Data Science 52

Mlearning.ai

SEPTEMBER 5, 2023

Our AI technologies meticulously sift through Big Data, capturing valuable nuggets often overlooked by traditional dashboards and reports. This report not only ranks your insights but deciphers them too, courtesy of eXplainable AI. First, automated insight detection.

Business Intelligence 52

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Pickl AI

JULY 14, 2023

Big Data and Deep Learning (2010s-2020s): The availability of massive amounts of data and increased computational power led to the rise of Big Data analytics. Robotics also witnessed advancements, with AI-powered robots becoming more capable in navigation, manipulation, and interaction with the physical world.

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Pickl AI

JANUARY 13, 2025

It simplifies complex AI topics like clustering , dimensionality , and regression , providing practical examples and numeric calculations to enhance understanding. Key Features: Explains AI algorithms like clustering and regression. Explains big datas role in AI. Discusses structuring Big Data for AI.

Artificial Intelligence 52

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Marktechpost

AUGUST 24, 2023

In the fast-paced world of Artificial Intelligence (AI) and Machine Learning, staying updated with the latest trends, breakthroughs, and discussions is crucial. Here’s our curated list of the top AI and Machine Learning-related subreddits to follow in 2023 to keep you in the loop.

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Ofemwire

MARCH 1, 2024

B – Big Data : Large volumes of structured and unstructured data that inundates a business on a day-to-day basis. It’s what organizations do with the data that matters—data analytics and AI are key to extracting insights from big data.

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Pickl AI

SEPTEMBER 17, 2024

Read More: Big Data and Artificial Intelligence: How They Work Together? 15 AI Interview Questions and Answers Interview questions for Artificial Intelligence positions often delve into a wide range of topics, from fundamental principles to cutting-edge techniques. What Is the Role of Explainable AI (XAI) In Machine Learning?

Artificial Intelligence 52

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Pickl AI

JULY 24, 2024

The combination of increased computational power and innovative algorithms laid the foundation for the next wave of AI advancements. AI in the 21st Century The 21st century has witnessed an unprecedented boom in AI research and applications. 2011: IBM Watson defeats Ken Jennings on the quiz show “Jeopardy!

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The MLOps Blog

JUNE 27, 2023

Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture. Delta Lake Delta Lake is an open-source storage layer that provides reliability, ACID transactions, and data versioning for big data processing frameworks such as Apache Spark.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

You can also extend this solution by bringing in your own data sources and modeling frameworks. She is passionate about developing, deploying, and explaining AI/ ML solutions across various domains. She holds a master’s degree in Computer Science specialized in Data Science from the University of Colorado, Boulder.

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Dlabs.ai

MAY 22, 2022

The first is for Data Scientists / Machine Learning Engineers, consisting of eight parts: Big Data & Machine Learning Fundamentals Perform Foundational Data, ML, and AI Tasks in Google Cloud Machine Learning on Google Cloud Advanced Machine Learning with TensorFlow on Google Cloud Platform MLOps (Machine Learning Operations) Fundamentals ML Pipelines (..)

Artificial Intelligence 52

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AI News

APRIL 25, 2024

In an interview ahead of the AI & Big Data Expo North America , Igor Jablokov, CEO and founder of AI company Pryon , addressed these pressing issues head-on. This allows organisations to ring-fence highly sensitive data behind their own firewalls when needed. And guess what?

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The MLOps Blog

AUGUST 11, 2023

Standard ML pipeline | Source: Author Advantages and disadvantages of directed acyclic graphs architecture Using DAGs provides an efficient way to execute processes and tasks in various applications, including big data analytics, machine learning, and artificial intelligence, where task dependencies and the order of execution are crucial.

ML 52

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Unite.AI

MARCH 5, 2025

Jamie Twiss is an experienced banker and a data scientist who works at the intersection of data science, artificial intelligence, and consumer lending. He currently serves as the Chief Executive Officer of Carrington Labs , a leading provider of explainable AI-powered credit risk scoring and lending solutions.

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Unite.AI

JULY 5, 2024

Establishing strong information governance frameworks ensures data quality, security and regulatory compliance. This includes defining data standards, policies and processes for data management, as well as leveraging advanced analytics and big data technologies to extract actionable insights from health data.

Data Integration 147

Data Integration Data Quality Algorithm AI Modeling 147

Pickl AI

APRIL 2, 2024

Understanding Data Structured Data: Organized data with a clear format, often found in databases or spreadsheets. Unstructured Data: Data without a predefined structure, like text documents, social media posts, or images. Data Cleaning: Process of identifying and correcting errors or inconsistencies in datasets.

Data Science 52

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ODSC - Open Data Science

MARCH 1, 2024

This part of the session equips participants with the ‘blocks’ necessary to construct sophisticated AI models, including those based on machine learning, deep learning, and Explainable AI. It’s an opportunity to see the versatility of KNIME’s AI tools in action, offering a glimpse into the potential of GeoAI applications.

Data Science 52

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