AssemblyAI

JULY 18, 2023

Building on In-House Hardware Conformer-2 was trained on our own GPU compute cluster of 80GB-A100s. To do this, we deployed a fault-tolerant and highly scalable cluster management and job scheduling Slurm scheduler, capable of managing resources in the cluster, recovering from failures, and adding or removing specific nodes.

Clustering 98

Clustering Supervised Learning AI AI 98

Snorkel AI

AUGUST 15, 2024

Now imagine someone asked you the same question while you held a history book with a list of presidents and their dates served. Data scientists train embedding models on unstructured text through a process called “self-supervised learning.” Let’s go back to our history book analogy. That’s how RAG works.

Database 52

Database Clustering Supervised Learning AI 52

Snorkel AI

AUGUST 15, 2024

Now imagine someone asked you the same question while you held a history book with a list of presidents and their dates served. Data scientists train embedding models on unstructured text through a process called “self-supervised learning.” Let’s go back to our history book analogy. That’s how RAG works.

Database 52

Database Clustering Supervised Learning AI 52

Snorkel AI

OCTOBER 6, 2023

Pre-training with unstructured data Pre-training with unstructured data sounds simple: gather proprietary data from across your organization and dump it all into a self-supervised learning pipeline. See what Snorkel can do to accelerate your data science and machine learning teams. Book a demo today.

Data Science 69

Data Science Supervised Learning Data Mining Data Mining 69

Snorkel AI

OCTOBER 6, 2023

Pre-training with unstructured data Pre-training with unstructured data sounds simple: gather proprietary data from across your organization and dump it all into a self-supervised learning pipeline. See what Snorkel can do to accelerate your data science and machine learning teams. Book a demo today.

Data Science 59

Data Science Supervised Learning Data Mining Data Mining 59

Pickl AI

MAY 31, 2023

How to Learn Python for Data Science in 5 Steps In order to learn Python for Data Science, following are the 5 basic steps that you need to follow: Learn the Fundamentals of Python: Learn the basic principles of the Python programming language. It includes regression, classification, clustering, decision trees, and more.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Snorkel AI

OCTOBER 6, 2023

Pre-training with unstructured data Pre-training with unstructured data sounds simple: gather proprietary data from across your organization and dump it all into a self-supervised learning pipeline. Book a demo today. But it’s not that straightforward. Data scientists can clean this up ahead of pre-training in a number of ways.

Data Scientist 52

Data Scientist Data Science Supervised Learning Data Mining 52

Pickl AI

OCTOBER 20, 2024

For example, You can learn Python on Pickl.AI Books : “Automate the Boring Stuff with Python” is excellent for those who prefer self-paced learning. Deep Learning is a subset of ML. Unsupervised learning focuses on uncovering hidden patterns in unlabeled data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Dataconomy

JULY 30, 2024

For those who are non-tech-savvy , machine learning, a cornerstone of artificial intelligence, trains computers to interpret data and make decisions. It’s divided primarily into three types: supervised, unsupervised, and reinforcement learning.

Algorithm 169

Algorithm AI AI Machine Learning 169

Flipboard

DECEMBER 6, 2023

The model then uses a clustering algorithm to group the sentences into clusters. The sentences that are closest to the center of each cluster are selected to form the summary. Implementation includes the following steps: The first step is to break down the large document, such as a book, into smaller sections, or chunks.

AWS 166

AWS Clustering Artificial Intelligence Artificial Intelligence 166

How to Learn Machine Learning

MARCH 25, 2025

At the core of machine learning, two primary learning techniques drive these innovations. These are known as supervised learning and unsupervised learning. Supervised learning and unsupervised learning differ in how they process data and extract insights.

Supervised Learning 59

Supervised Learning Machine Learning Machine Learning Algorithm 59