ODSC - Open Data Science

FEBRUARY 13, 2023

Top 3 Free Training Sessions Microsoft Azure: Machine Learning Essentials This series of videos from Microsoft covers the entire stack of machine learning essentials with Microsoft Azure. A few standout topics include model deployment and inferencing, MLOps, and multi-cloud machine learning.

Machine Learning 98

Machine Learning Machine Learning Deep Learning Deep Learning 98

Mlearning.ai

JUNE 14, 2023

Deploy LLMs in production Deploy Model Azure —  Use endpoints for inference — Azure Machine Learning | Microsoft Learn AWS + Huggingface —  Exporting ? Transformers (huggingface.co) Training Sentiment Model Using BERT and Serving it with Flask API — YouTube 5.

Natural Language Processing 52

Natural Language Processing ML ML Support Vector Machines 52

Pickl AI

JULY 12, 2024

Support Vector Machines (SVM) SVMs classify data points by finding the optimal hyperplane that maximises the margin between classes. Popular models include decision trees, support vector machines (SVM), and neural networks. classification, regression) and data characteristics.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

NOVEMBER 28, 2024

Support Vector Machines (SVM) SVMs are powerful classifiers that separate data into distinct categories by finding an optimal hyperplane. Cloud platforms like AWS , Google Cloud Platform (GCP), and Microsoft Azure provide managed services for Machine Learning, offering tools for model training, storage, and inference at scale.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

APRIL 21, 2024

Scikit-learn provides a consistent API for training and using machine learning models, making it easy to experiment with different algorithms and techniques. Similar to SageMaker, Azure ML offers a range of tools and services for the entire machine learning lifecycle, from data preparation and model development to deployment and monitoring.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Dataconomy

MARCH 13, 2023

Here are some of the essential tools and platforms that you need to consider: Cloud platforms Cloud platforms such as AWS , Google Cloud , and Microsoft Azure provide a range of services and tools that make it easier to develop, deploy, and manage AI applications.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

ODSC - Open Data Science

JANUARY 7, 2025

Core Machine Learning Algorithms Core machine learning algorithms remain foundational for data science workflows. Classification techniques like random forests, decision trees, and support vector machines are among the most widely used, enabling tasks such as categorizing data and building predictive models.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40