IBM Journey to AI blog

AUGUST 15, 2023

A common phrase you’ll hear around AI is that artificial intelligence is only as good as the data foundation that shapes it. Therefore, a well-built AI for business program must also have a good data governance framework. Doing so allows your organization the ability to scale with trust and transparency.

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Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

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AWS Machine Learning Blog

OCTOBER 2, 2024

This includes implementing access controls, data governance policies, and proactive monitoring and alerting to make sure sensitive information is properly secured and monitored. For cases where you need a semantic understanding of your data, you can use Amazon Kendra for intelligent enterprise search.

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insideBIGDATA

JUNE 25, 2024

Carey School of Business), and Marc Eulerich (University of Duisberg-Essen) Mercator School of Management), announced the Enterprise GenAI Governance Framework — the first-ever enterprise risk framework for generative artificial intelligence (GenAI).

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The MLOps Blog

JUNE 27, 2023

It sits between the data lake and cloud object storage, allowing you to version and control changes to data lakes at scale. LakeFS facilitates data reproducibility, collaboration, and data governance within the data lake environment. Monitor the performance of machine learning models.

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AWS Machine Learning Blog

MAY 9, 2024

Data governance – With a wide variety of users accessing the platform and with different users having access to different data, data governance and isolation was paramount. As a fully managed service, Verisk took advantage of its deep-learning search models without additional provisioning.

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Heartbeat

DECEMBER 7, 2023

What are the new data governance trends, “Data Fabric” and “Data Mesh”? I decided to write a series of blogs on current topics: the elements of data governance that I have been thinking about, reading, and following for a while. Advantages: Consistency ensures trust in data governance.

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Data Science Dojo

AUGUST 24, 2023

While Metaflow has several strengths, there are certain areas where it may lack or fall short when compared to other MLOps tools: Limited deep learning support : Metaflow was initially developed to focus on typical data science workflows and traditional ML methods rather than deep learning.

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Pickl AI

SEPTEMBER 17, 2024

Some of the key future trends include: Increased Use of Deep Learning and Neural Networks As computing power and data availability continue to grow, we can expect to see more advanced Deep Learning models being applied to cybersecurity challenges, enabling even more accurate threat detection and prediction.

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IBM Journey to AI blog

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

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Heartbeat

OCTOBER 23, 2023

Image and Signal Processing: In medical imaging and signal processing, data scientists and machine learning engineers employ advanced algorithms to extract valuable information from images, such as CT scans, MRIs, and EKGs. We're committed to supporting and inspiring developers and engineers from all walks of life.

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Heartbeat

MAY 29, 2023

Hyperparameters are the configuration variables of a machine learning algorithm that are set prior to training, such as learning rate, number of hidden layers, number of neurons per layer, regularization parameter, and batch size, among others.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

Improve the quality and time to market for deep learning models in diagnostic medical imaging. Data Management – Efficient data management is crucial for AI/ML platforms. Regulations in the healthcare industry call for especially rigorous data governance.

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DagsHub

AUGUST 23, 2024

We already know that a data quality framework is basically a set of processes for validating, cleaning, transforming, and monitoring data. Data Governance Data governance is the foundation of any data quality framework. It primarily caters to large organizations with complex data environments.

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DagsHub

FEBRUARY 29, 2024

Data preparation involves multiple processes, such as setting up the overall data ecosystem, including a data lake and feature store, data acquisition and procurement as required, data annotation, data cleaning, data feature processing and data governance. link] | [link] | [link]

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AWS Machine Learning Blog

JANUARY 13, 2023

In recent years, this new learning paradigm has been successfully adopted to address the concern of data governance in training ML models. This allows you to train an ML model on distributed data, without the need to share or move it. This iterative process of model training continues until the global model converges.

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Pickl AI

DECEMBER 4, 2023

Exploring technologies like Data visualization tools and predictive modeling becomes our compass in this intricate landscape. Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence.

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AWS Machine Learning Blog

JUNE 5, 2023

Lake Formation automatically manages access to the registered data in Amazon S3 through services including AWS Glue , Athena, Amazon Redshift, Amazon QuickSight , and Amazon EMR using Zeppelin notebooks with Apache Spark to ensure compliance with your defined policies. The imported datasets contain targeted and related time series data.

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Pickl AI

APRIL 2, 2024

Machine Learning: Subset of AI that enables systems to learn from data without being explicitly programmed. Supervised Learning: Learning from labeled data to make predictions or decisions. Unsupervised Learning: Finding patterns or insights from unlabeled data.

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DagsHub

SEPTEMBER 23, 2024

However, deep learning architectures—particularly transformer models, which are infamously opaque—are the foundation of LLMs. This includes creating clear policies for data handling that align with relevant regulations ensuring that all data processing activities are transparent and documented.

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How to Learn Machine Learning

APRIL 23, 2023

Machine learning demands continuous evolution in business processes, starting with businesses’ capacity to adapt to rapid changes, evolving skill sets, and diverse growth opportunities. These processes ensure all data are evaluated and all scopes are checked, tested, and assessed.

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Pickl AI

AUGUST 9, 2024

Unsupervised Learning Exploring clustering techniques like k-means and hierarchical clustering, along with dimensionality reduction methods such as PCA (Principal Component Analysis). Students should understand how to identify patterns in unlabeled data. Students should learn about neural networks and their architecture.

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AWS Machine Learning Blog

JANUARY 13, 2023

We call the data loader function for eICU data with the following code: elif dataset_name == "eicu": logging.info("load_data. FedML supports several out-of-the-box deep learning algorithms for various data types, such as tabular, text, image, graphs, and Internet of Things (IoT) data. Define the model.

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Defined.ai blog

AUGUST 10, 2023

Data Quality For AI to produce reliable results, it needs high-quality data. Ensuring accurate, relevant, complete, and up-to-date data is essential. Regular data audits and implementing robust data governance practices can help maintain data quality.

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Pickl AI

JULY 25, 2023

Skills and Tools of Data Scientists To excel in the field of Data Science, professionals need a diverse skill set, including: Programming Languages: Python, R, SQL, etc. Machine Learning: Supervised and unsupervised learning techniques, deep learning, etc. Big Data Technologies: Hadoop, Spark, etc.

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Pickl AI

APRIL 26, 2024

I contributed by providing data insights, developing predictive models, and presenting findings, ultimately leading to more targeted marketing strategies and increased customer engagement. Data Governance and Ethics Questions What is data governance, and why is it important?

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ODSC - Open Data Science

APRIL 21, 2023

With its applications in creativity, automation, business, advancements in NLP, and deep learning, the technology isn’t only opening new doors, but igniting the public imagination. Let’s take a look at what’s in store for you at ODSC East this May 9th-11th and what you’ll learn about generative AI when you attend.

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DagsHub

OCTOBER 23, 2024

It allows users to extract data from documents, and then you can configure workflows to pass the data downstream to LLMs for further processing. Embedding Models Embedding models transform unstructured data, such as text, images , and audio, into vector representations.

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Data Science Blog

MARCH 14, 2023

Von Big Data über Data Science zu AI Einer der Gründe, warum Big Data insbesondere nach der Euphorie wieder aus der Diskussion verschwand, war der Leitspruch “S**t in, s**t out” und die Kernaussage, dass Daten in großen Mengen nicht viel wert seien, wenn die Datenqualität nicht stimme.

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Data Science Blog

MARCH 30, 2023

Eine bessere Idee ist es daher, Event Logs nicht in einzelnen Process Mining Tools aufzubereiten, sondern zentral in einem dafür vorgesehenen Data Warehouse zu erstellen, zu katalogisieren und darüber auch die grundsätzliche Data Governance abzusichern.

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AWS Machine Learning Blog

OCTOBER 11, 2024

Data lineage and auditing – Metadata can provide information about the provenance and lineage of documents, such as the source system, data ingestion pipeline, or other transformations applied to the data. This information can be valuable for data governance, auditing, and compliance purposes.

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