ODSC - Open Data Science

APRIL 13, 2023

5 Industries Using Synthetic Data in Practice Here’s an overview of what synthetic data is and a few examples of how various industries have benefited from it. Hands-on Data-Centric AI: Data Preparation Tuning — Why and How? Final ODSC East 2023 Schedule Released! Here’s how.

ML 52

ML ML Data Science Machine Learning 52

phData

DECEMBER 4, 2023

Thirty seconds is a good default for human users; if you find that queries are regularly queueing, consider making your warehouse a multi-cluster that scales on-demand. Cluster Count If your warehouse has to serve many concurrent requests, you may need to increase the cluster count to meet demand.

Clustering 98

Clustering Database SQL Data Pipeline 98

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Learning means identifying and capturing historical patterns from the data, and inference means mapping a current value to the historical pattern. The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference.

AWS 94

AWS ML ML Clustering 94

Pickl AI

NOVEMBER 28, 2024

billion in 2023 to $181.15 R and Other Languages While Python dominates, R is also an important tool, especially for statistical modelling and data visualisation. Unsupervised Learning Unsupervised learning involves training models on data without labels, where the system tries to find hidden patterns or structures.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

ODSC - Open Data Science

JANUARY 29, 2024

Fine-tuning is important for applying domain-specific knowledge to an existing LLM which provides better performance and prompt results Inference Efficiency An emergent skill in late 2023, its inclusion speaks to its importance. Stable Diffusion seems favored, perhaps due to it being largely an open-source model.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

Pickl AI

NOVEMBER 4, 2024

They facilitate complex calculations, trend analysis, and data modelling, making them essential for generating insights from the stored data. The global data warehouse as a service market was valued at USD 9.06 billion in 2023 and is projected to reach USD 55.96 The global data storage market was valued at USD 186.75

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Snorkel AI

MAY 26, 2023

And that’s really key for taking data science experiments into production. And then once you have access to this data, you’ll be able to process that data, whether it’s for data preparation, feature engineering, or data engineering, but also for model training and defining inference pipelines in Snowflake as well.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

And that’s really key for taking data science experiments into production. And then once you have access to this data, you’ll be able to process that data, whether it’s for data preparation, feature engineering, or data engineering, but also for model training and defining inference pipelines in Snowflake as well.

SQL 52

SQL ML ML Python 52

The MLOps Blog

MAY 9, 2023

Again, what goes on in this component is subjective to the data scientist’s initial (manual) data preparation process, the problem, and the data used. Mihir Mathur, Product Manager at Lyft, in “Powering Millions of Real-Time Decisions with LyftLearn Serving” blog 2023.

ML 98

ML ML Machine Learning Machine Learning 98

AWS Machine Learning Blog

SEPTEMBER 18, 2024

Context In early 2023, Zeta’s machine learning (ML) teams shifted from traditional vertical teams to a more dynamic horizontal structure, introducing the concept of pods comprising diverse skill sets. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly.

AWS 111

AWS Machine Learning Machine Learning ML 111

DagsHub

JULY 15, 2024

Gemini series : Gemini was developed by Google DeepMind and was introduced in 2023. Data Management Costs Data Collection : Involves sourcing diverse datasets, including multilingual and domain-specific corpora, from various digital sources, essential for developing a robust LLM.

Azure 52

Azure AI AI Database 52

AWS Machine Learning Blog

DECEMBER 19, 2024

Data preprocessing Text data can come from diverse sources and exist in a wide variety of formats such as PDF, HTML, JSON, and Microsoft Office documents such as Word, Excel, and PowerPoint. Its rare to already have access to text data that can be readily processed and fed into an LLM for training.

AWS 86

AWS Machine Learning Machine Learning Natural Language Processing 86