KDnuggets

DECEMBER 14, 2021

We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.

Data Science 399

Data Science Machine Learning Machine Learning Analytics 399

Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. AWS also offers developers the technology to develop smart apps using machine learning and complex algorithms.

AWS 138

AWS Cloud Computing Data Lakes Database 138

Flipboard

MARCH 7, 2023

Then the transcripts of contacts become available to CSBA to extract actionable insights through millions of customer contacts for the sellers, and the data is stored in the Seller Data Lake. Here, a non-deep learning model was trained and run on SageMaker, the details of which will be explained in the following section.

ML 123

ML ML AWS AI 123

AWS Machine Learning Blog

SEPTEMBER 5, 2023

We first highlight how we use AWS Glue for highly parallel data processing. We then discuss how Amazon SageMaker helps us with feature engineering and building a scalable supervised deep learning model. Dan Volk is a Data Scientist at the AWS Generative AI Innovation Center. Kexin Ding is a fifth-year Ph.D.

AWS 122

AWS ML ML Machine Learning 122

AWS Machine Learning Blog

SEPTEMBER 1, 2023

ML operationalization summary As defined in the post MLOps foundation roadmap for enterprises with Amazon SageMaker , ML and operations (MLOps) is the combination of people, processes, and technology to productionize machine learning (ML) solutions efficiently. For them, the end-to-end MLOps lifecycle and infrastructure is necessary.

AI 127

AI AI ML ML 127

How to Learn Machine Learning

MAY 2, 2025

Advanced Capabilities and Use Cases of Azure Machine Learning Handling Different Data Types Azure Machine Learning excels at working with various data types: Structured Data : Traditional tabular data can be processed using AutoML or custom models with frameworks like scikit-learn or XGBoost.

Azure 52

Azure Machine Learning Machine Learning Data Science 52

AWS Machine Learning Blog

NOVEMBER 12, 2024

He is focused on Big Data, Data Lakes, Streaming and batch Analytics services and generative AI technologies. The results are similar to fine-tuning LLMs without the complexities of fine-tuning models. He is actively working on projects in the ML space and has presented at numerous conferences including Strata and GlueCon.

SQL 112

SQL AWS AI AI 112

IBM Journey to AI blog

MAY 9, 2023

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. models are trained on IBM’s curated, enterprise-focused data lake, on our custom-designed cloud-native AI supercomputer, Vela. All watsonx.ai

AI 139

AI AI Data Quality Data Lakes 139

Flipboard

NOVEMBER 24, 2023

Data scientists and ML engineers require capable tooling and sufficient compute for their work. Therefore, BMW established a centralized ML/deep learning infrastructure on premises several years ago and continuously upgraded it.

ML 153

ML ML AWS AI 153

ODSC - Open Data Science

NOVEMBER 19, 2024

Here’s a breakdown of ten top sessions from this year’s conference that data professionals should consider. Topological Deep Learning Made Easy with TopoX with Dr. Mustafa Hajij Slides In these AI slides, Dr. Mustafa Hajij introduced TopoX, a comprehensive Python suite for topological deep learning.

Deep Learning 52

Deep Learning Deep Learning Data Science AI 52

The MLOps Blog

JUNE 27, 2023

LakeFS LakeFS is an open-source platform that provides data lake versioning and management capabilities. It sits between the data lake and cloud object storage, allowing you to version and control changes to data lakes at scale. Monitor the performance of machine learning models.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

ODSC - Open Data Science

JULY 22, 2023

Keynotes Our main keynote sessions were held on the virtual side of the conference.

Apache Kafka 52

Apache Kafka Machine Learning Machine Learning Data Science 52

ODSC - Open Data Science

FEBRUARY 2, 2023

As you’ll see in the next section, data scientists will be expected to know at least one programming language, with Python, R, and SQL being the leaders. This will lead to algorithm development for any machine or deep learning processes.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

ODSC - Open Data Science

MARCH 11, 2024

NLP and LLMs The NLP and LLMs track will give you the opportunity to learn firsthand from core practitioners and contributors about the latest trends in data science languages and tools, such as pre-trained models, with use cases focusing on deep learning, speech-to-text, and semantic search.

Data Science 52

Data Science Deep Learning Deep Learning Machine Learning 52

ODSC - Open Data Science

MARCH 23, 2023

Open-source Data Lake Management, Curation, and Governance for New and Growing Companies Arjuna Chala, Associate Vice President at HPCC Systems and Special Projects, discusses the challenges associated with managing data lake technology for start-ups and rapidly-growing companies. Watch on-demand here.

Data Science 52

Data Science Data Lakes Machine Learning Machine Learning 52

ODSC - Open Data Science

AUGUST 24, 2023

MIT Researchers Combine Deep Learning and Physics to Fix MRI Scans MIT researchers are now armed with a new deep learning model that is designed to rectify motion-related distortions in brain MRI. Register now for 50% off.

Data Lakes 52

Data Lakes Data Science Machine Learning Machine Learning 52

ODSC - Open Data Science

MAY 8, 2023

To get the data, you will need to follow the instructions in the article: Create a Data Solution on Azure Synapse Analytics with Snapshot Serengeti — Part 1 — Microsoft Community Hub, where you will load data into Azure Data Lake via Azure Synapse. Lastly, upload the data from Azure Subscription.

Azure 52

Azure ML ML Data Modeling 52

IBM Journey to AI blog

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. models are trained on IBM’s curated, enterprise-focused data lake. That’s where the foundation model enters the picture. All watsonx.ai

AI 70

AI AI Machine Learning Machine Learning 70

AWS Machine Learning Blog

DECEMBER 18, 2023

SageMaker Canvas supports a number of use cases, including time-series forecasting , which empowers businesses to forecast future demand, sales, resource requirements, and other time-series data accurately. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

Clustering 122

Clustering AWS Database ML 122

ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

Azure 52

Azure ML ML Data Modeling 52

IBM Journey to AI blog

JUNE 14, 2023

Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. You need to collect, curate, and annotate data for any specific task you want to perform. Sometimes the problem with artificial intelligence (AI) and automation is that they are too labor intensive.

AI 103

AI AI Natural Language Processing Data Lakes 103

ODSC - Open Data Science

JULY 14, 2023

The session participants will learn the theory behind compound sparsity, state-of-the-art techniques, and how to apply it in practice using the Neural Magic platform. You’ll also discuss different popular large language models and compare the techniques and accuracy of results among different large language models.

Machine Learning 52

Machine Learning Machine Learning Apache Kafka Data Science 52

ODSC - Open Data Science

JUNE 7, 2023

Wednesday, June 14th Me, my health, and AI: applications in medical diagnostics and prognostics: Sara Khalid | Associate Professor, Senior Research Fellow, Biomedical Data Science and Health Informatics | University of Oxford Iterated and Exponentially Weighted Moving Principal Component Analysis : Dr. Paul A.

Apache Kafka 52

Apache Kafka Machine Learning Machine Learning Data Science 52

Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. If you want to do the process in a low-code/no-code way, you can follow option C.

ML 123

ML ML AWS Data Warehouse 123

ODSC - Open Data Science

NOVEMBER 18, 2024

Dimensional Data Modeling in the Modern Era Dustin Dorsey |Principal Data Architect |Onix With the emergence of big data, cloud computing, and AI-driven analytics, many wonder if the traditional principles of dimensional modeling still hold value.

Deep Learning 40

Deep Learning Deep Learning Database Data Science 40

IBM Journey to AI blog

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments.

AI 110

AI AI Data Warehouse Machine Learning 110

DagsHub

NOVEMBER 11, 2024

These vector databases store complex data by transforming the original unstructured data into numerical embeddings; this is enabled through deep learning models. As reiterated earlier, embeddings take the critical components of various kinds of data, like text, images, and audio, and project them into one vector space.

AI 52

AI AI Data Lakes Database 52

Flipboard

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data.

AWS 123

AWS ML ML ETL 123

ODSC - Open Data Science

APRIL 3, 2023

Data analysts often must go out and find their data, process it, clean it, and get it ready for analysis. This pushes into Big Data as well, as many companies now have significant amounts of data and large data lakes that need analyzing.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

DagsHub

OCTOBER 23, 2024

To combine the collected data, you can integrate different data producers into a data lake as a repository. A central repository for unstructured data is beneficial for tasks like analytics and data virtualization. Data Cleaning The next step is to clean the data after ingesting it into the data lake.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

O'Reilly Media

OCTOBER 19, 2021

This introduces further requirements: The scale of operations is often two orders of magnitude larger than in the earlier data-centric environments. Not only is data larger, but models—deep learning models in particular—are much larger than before. Compute.

ML 145

ML ML Data Scientist AWS 145

AWS Machine Learning Blog

NOVEMBER 22, 2023

Mai-Lan Tomsen Bukovec, Vice President, Technology | AIM250-INT | Putting your data to work with generative AI Thursday November 30 | 12:30 PM – 1:30 PM (PST) | Venetian | Level 5 | Palazzo Ballroom B How can you turn your data lake into a business advantage with generative AI? Reserve your seat now!

AWS 137

AWS ML ML AI 137

DataRobot Blog

MARCH 7, 2023

The DataRobot AI Platform seamlessly integrates with Azure cloud services, including Azure Machine Learning, Azure Data Lake Storage Gen 2 (ADLS), Azure Synapse Analytics, and Azure SQL database. The capability to rapidly build an AI-powered organization with industry-specific solutions and expertise.

Azure 59

Azure Machine Learning Machine Learning AI 59

Pickl AI

AUGUST 9, 2024

Data Lake vs. Data Warehouse Distinguishing between these two storage paradigms and understanding their use cases. Students should learn how data lake s can store raw data in its native format, while data warehouses are optimised for structured data.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Iguazio

JANUARY 16, 2024

The system’s architecture ensures the data flows through the different systems effectively. First, the data lake is fed from a number of data sources. These include conversational data, ATS Data and more. For example: Building a comprehensive and sophisticated AI chatbot.

ML 52

ML ML DataOps Data Scientist 52

Iguazio

JANUARY 16, 2024

The system’s architecture ensures the data flows through the different systems effectively. First, the data lake is fed from a number of data sources. These include conversational data, ATS data, and more. In addition, Sense plans to use Iguazio for a future product called Sense co-pilot.

ML 52

ML ML DataOps Data Scientist 52

AWS Machine Learning Blog

JUNE 22, 2023

In LnW Connect, an encryption process was designed to provide a secure and reliable mechanism for the data to be brought into an AWS data lake for predictive modeling. The final model ingests historical machine event sequence data, time features such as hour of the day, and static machine metadata.

AWS 110

AWS ML ML Machine Learning 110