The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. For example, if your team is proficient in Python and R, you may want an MLOps tool that supports open data formats like Parquet, JSON, CSV, etc., neptune.ai

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Viso.ai

MARCH 29, 2024

Streamlit is a good choice for developers and teams that are well-versed in data science and want to deploy AI models easily, and quickly, with a few lines of code. About us: At viso.ai, we’ve built the end-to-end machine learning infrastructure for enterprises to scale their computer vision applications easily.

Computer Vision 52

Computer Vision Auto-classification Machine Learning Python 52

Heartbeat

DECEMBER 27, 2023

Docker makes machine learning workloads portable and reproducible. These Python virtual environments encapsulate and manage Python dependencies, while Docker encapsulates the project’s dependency stack down to the host OS. These Python virtual environments encapsulate and manage Python dependencies.

Machine Learning 52

Machine Learning Python ML Categorization 52

Flipboard

AUGUST 17, 2023

If you are prompted to choose a kernel, choose Data Science as the image and Python 3 as the kernel, then choose Select. as the image and Glue Python [PySpark and Ray] as the kernel, then choose Select. Here is one end-to-end data flow in the scenario of PLACE feature engineering.

ML 93

ML Auto-complete Auto-classification Machine Learning 93

Google Research AI blog

FEBRUARY 28, 2023

Through exploreCSR , we partner with universities to provide students with introductory experiences in research, such as Rice University’s regional workshop on applications and research in data science (ReWARDS), which was delivered in rural Peru by faculty from Rice. See some of the datasets and tools we released in 2022 listed below.

Robotics 72

Robotics Deep Learning Auto-classification ML 72

AWS Machine Learning Blog

MARCH 1, 2023

To solve this problem, we make the ML solution auto-deployable with a few configuration changes. Data pipeline for ML feature generation Game logs stored in Athena backed by Amazon S3 go through the ETL pipelines created as Python shell jobs in AWS Glue. AutoGluon is a toolkit for automated machine learning (AutoML).

Automation 92

Automation ETL Data Drift ML 92

Dlabs.ai

JANUARY 16, 2023

Kaggle is an online community for data scientists that regularly organizes data science contests. The Mayo Clinic sponsored the Mayo Clinic – STRIP AI competition focused on image classification of stroke blood clot origin. Unfortunately, the competition rules prevent us from publishing competition data publicly.

Neural Network 52

Neural Network ML Auto-classification Convolutional Neural Networks 52

AWS Machine Learning Blog

JANUARY 31, 2024

In the first part of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. We provide guidance on building, training, and deploying deep learning networks on Amazon SageMaker.

Computer Vision 95

Computer Vision Auto-complete Deep Learning Auto-classification 95

AWS Machine Learning Blog

NOVEMBER 1, 2023

The system is further refined with DistilBERT , optimizing our dialogue-guided multi-class classification process. Utilizing the latest Hugging Face LLM modules on Amazon SageMaker, AWS customers can now tap into the power of SageMaker deep learning containers (DLCs). TGI is implemented in Python and uses the PyTorch framework.

Auto-classification 97

Auto-classification LLM Auto-complete Generative AI 97

AWS Machine Learning Blog

JANUARY 9, 2023

For example, an image classification use case may use three different models to perform the task. The scatter-gather pattern allows you to combine results from inferences run on three different models and pick the most probable classification model. These endpoints are fully managed and support auto scaling.

ML 78

ML Auto-complete Auto-classification Deep Learning 78