Alation

MAY 26, 2022

Without care and feeding of the data, trust erodes and use of the data becomes impossible. We need to do things to make data better. Some of that is done automatically with tools, AI/ML, or just better processes, but much of it requires manual work somewhere by someone — and sometime soon! Stage 2: Grouchiness.

Data Governance 52

Data Governance Clean Data ML ML 52

Tableau

OCTOBER 8, 2021

With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics. Connecting directly to this semantic layer will help give customers access to critical business data in a safe, governed manner.

Tableau 98

Tableau Analytics Analytics Machine Learning 98

AWS Machine Learning Blog

NOVEMBER 30, 2023

AWS innovates to offer the most advanced infrastructure for ML. For ML specifically, we started with AWS Inferentia, our purpose-built inference chip. Neuron plugs into popular ML frameworks like PyTorch and TensorFlow, and support for JAX is coming early next year. Customers like Adobe, Deutsche Telekom, and Leonardo.ai

AWS 136

AWS AI AI ML 136

Mlearning.ai

JUNE 28, 2023

You know that there is a vocabulary exam type of question in SAT that asks for the correct definition of a word that is selected from the passage that they provided. The AI generates questions asking for the definition of the vocabulary that made it to the end after the entire filtering process. So I tried to think of something else.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing AI 52

Flipboard

JULY 10, 2023

Figure 3 illustrates the visualization of the latent space and the process we discussed in the story, which aligns with the technical definition of the encoder and decoder. It works well for simple data but may struggle with complex patterns. Alex then reconstructs the item using the same or a very similar location.

Deep Learning 132

Deep Learning Deep Learning Machine Learning Machine Learning 132

DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. What is Unstructured Data?

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

DagsHub

FEBRUARY 29, 2024

Typically, flashy new algorithms or state-of-the-art models capture both public imagination and the interest of data scientists, but messy data can undermine even the most sophisticated model. For instance, bad data is reported to cost the US $3 Trillion per year and poor quality data costs organizations an average of $12.9

Data Preparation 52

Data Preparation Machine Learning Machine Learning Data Governance 52

Mlearning.ai

MAY 23, 2023

The following figure represents the life cycle of data science. It starts with gathering the business requirements and relevant data. Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Why is data cleaning crucial?

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

JULY 8, 2024

These pipelines automate collecting, transforming, and delivering data, crucial for informed decision-making and operational efficiency across industries. Tools such as Python’s Pandas library, Apache Spark, or specialised data cleaning software streamline these processes, ensuring data integrity before further transformation.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

Snorkel AI

JULY 3, 2023

Python’s definitely the most popular. I guess if you’re using deep learning—in your case, I guess it’s tabular data, so you don’t really need the large deep learning models. That would be an interesting extension and I would love to actually play with that. AB : Makes sense. JG : Exactly. AB : Makes sense.

Data Pipeline 52

Data Pipeline Exploratory Data Analysis Data Scientist Machine Learning 52

Snorkel AI

JULY 3, 2023

Python’s definitely the most popular. I guess if you’re using deep learning—in your case, I guess it’s tabular data, so you don’t really need the large deep learning models. That would be an interesting extension and I would love to actually play with that. AB : Makes sense. JG : Exactly. AB : Makes sense.

Data Pipeline 52

Data Pipeline Exploratory Data Analysis Data Scientist Machine Learning 52

AWS Machine Learning Blog

DECEMBER 19, 2024

output_first_template = '''Given the classification task definition and the class labels, generate an input that corresponds to each of the class labels. From extracting and cleaning data from diverse sources to deduplicating content and maintaining ethical standards, each step plays a crucial role in shaping the models performance.

AWS 88

AWS Machine Learning Machine Learning Natural Language Processing 88