ODSC - Open Data Science

OCTOBER 4, 2024

His research includes developing algorithms for end-to-end training of deep neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, and deep reinforcement learning algorithms. His career has spanned both technology and government. Sign me up!

Data Science 52

Data Science Machine Learning Machine Learning Algorithm 52

AWS Machine Learning Blog

JULY 13, 2023

Another way can be to use an AllReduce algorithm. For example, in the ring-allreduce algorithm, each node communicates with only two of its neighboring nodes, thereby reducing the overall data transfers. Train a binary classification model using the SageMaker built-in XGBoost algorithm. arXiv preprint arXiv:1609.04836 (2016). [3]

Clustering 97

Clustering Algorithm Deep Learning Deep Learning 97

AWS Machine Learning Blog

APRIL 18, 2023

To make things easy, these three inputs depend solely on the model name, version (for a list of the available models, see Built-in Algorithms with pre-trained Model Table ), and the type of instance you want to train on. learning_rate – Controls the step size or learning rate of the optimization algorithm during training.

ML 96

ML ML Deep Learning Deep Learning 96

DagsHub

JULY 25, 2024

TensorFlow implements a wide range of deep learning and machine learning algorithms and is well-known for its adaptability and extensive ecosystem. In finance, it's applied for fraud detection and algorithmic trading. Founded in 2016, HuggingFace has strongly impacted the field of NLP with its easy-to-use APIs and pre-trained models.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

IBM Journey to AI blog

SEPTEMBER 11, 2023

It leverages machine learning algorithms to continuously learn and adapt to workload patterns, delivering superior performance and reducing administrative efforts. Db2 can run on Red Hat OpenShift and Kubernetes environments, ROSA & EKS on AWS, and ARO & AKS on Azure deployments. Overall, it is easier to deploy.

Database 101

Database SQL Data Warehouse Machine Learning 101

AWS Machine Learning Blog

APRIL 18, 2023

To make things easy, these three inputs depend solely on the model name, version (for a list of the available models, see Built-in Algorithms with pre-trained Model Table ), and the type of instance you want to train on. learning_rate – Controls the step size or learning rate of the optimization algorithm during training.

ML 52

ML ML Deep Learning Deep Learning 52

DagsHub

MARCH 19, 2024

In fact, the project's success also depends on various factors, such as: The algorithms and frameworks used The data used for training The performance metrics The deployment platform So, it's important that you manage your computer vision projects well to ensure success. How Do You Measure Success? and real-time inference is unnecessary.

Algorithm 52

Algorithm Deep Learning Deep Learning Data Engineering 52

DagsHub

APRIL 7, 2024

Image generated with Midjourney In today’s fast-paced world of data science, building impactful machine learning models relies on much more than selecting the best algorithm for the job. The project was created in 2014 by Airbnb and has been developed by the Apache Software Foundation since 2016.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Pickl AI

AUGUST 22, 2024

First released in 2016, it quickly gained traction due to its intuitive design and robust capabilities. Integration with Other Platforms and Services TensorFlow and PyTorch support integration with various platforms and services, including AWS, Google Cloud, and Azure. What is Transfer Learning in Deep Learning?

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Explosion

AUGUST 1, 2019

Based on the (fairly vague) marketing copy, AWS might be doing something similar in SageMaker. 2019) have shown that a transformer models trained on only 1% of the IMDB sentiment analysis data (just a few dozen examples) can exceed the pre-2016 state-of-the-art. Modern transfer learning techniques are bearing this out.

Natural Language Processing 52

Natural Language Processing Machine Learning Machine Learning AWS 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. This is accomplished by breaking the problem into independent parts so that each processing element can complete its part of the workload algorithm simultaneously.

AWS 112

AWS ML ML Clustering 112

AWS Machine Learning Blog

JANUARY 17, 2024

Today, we’re excited to announce the availability of Llama 2 inference and fine-tuning support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. In this post, we demonstrate how to deploy and fine-tune Llama 2 on Trainium and AWS Inferentia instances in SageMaker JumpStart.

AWS 127

AWS Python Machine Learning Machine Learning 127

AWS Machine Learning Blog

NOVEMBER 11, 2024

Prerequisites To try out this solution using SageMaker JumpStart, you’ll need the following prerequisites: An AWS account that will contain all of your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker. Default for Meta Llama 3.2 1B and Meta Llama 3.2 3B is False. Default for Meta Llama 3.2

AI 114

AI AI ML ML 114